OSGeo - User contributions [en]

Training Material for UN Open GIS Spiral 3

2020-07-01T00:33:57Z

Wiki-Somakang:

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the mentorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
===== 2.1.1. Install uDig SW =====
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

===== 2.1.2. Load "Processing Toolbox" plug-in =====
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.<br />
<b>*Name:</b> Processing Toolbox for uDig<br />
<b>*URL:</b> http://www.mangosystem.com:8080/s2toolbox_updates<br />
</div>
<br />

Now, lets’ load the Processing Toolbox into uDig.<br />
<b>Step1.</b> Set a location of repository for Processing Toolbox plug-in.<br />
[Help] --> [Find and Install] (Figure2): Install/Update window will pop up (Figure3) --> Click ‘Search for new features to install’ --> ‘Next’ button: Install window will pop up (Figure 4) --> Click ‘New Remote Site’ button à put repository Name and URL --> Click ‘OK’ button (Figure 5) --> Next button (Figure 6)

<b>Step 2.</b> Agree Feature License (Figure 7) <br />
<b>Step 3.</b> Loading plug-in (Figure 8) à Install all (Figure 9) à Restart (Figure 10)<br />
<b>Step 4.</b> View Processing Toolbox on uDig (Figure11- Figure 13)<br />

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:57:03Z

Wiki-Somakang: /* 2.1.2. Load "Processing Toolbox" plug-in */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

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== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
===== 2.1.1. Install uDig SW =====
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

===== 2.1.2. Load "Processing Toolbox" plug-in =====
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.<br />
<b>*Name:</b> Processing Toolbox for uDig<br />
<b>*URL:</b> http://www.mangosystem.com:8080/s2toolbox_updates<br />
</div>
<br />

Now, lets’ load the Processing Toolbox into uDig.<br />
<b>Step1.</b> Set a location of repository for Processing Toolbox plug-in.<br />
[Help] --> [Find and Install] (Figure2): Install/Update window will pop up (Figure3) --> Click ‘Search for new features to install’ --> ‘Next’ button: Install window will pop up (Figure 4) --> Click ‘New Remote Site’ button à put repository Name and URL --> Click ‘OK’ button (Figure 5) --> Next button (Figure 6)

<b>Step 2.</b> Agree Feature License (Figure 7) <br />
<b>Step 3.</b> Loading plug-in (Figure 8) à Install all (Figure 9) à Restart (Figure 10)<br />
<b>Step 4.</b> View Processing Toolbox on uDig (Figure11- Figure 13)<br />

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:56:41Z

Wiki-Somakang: /* 2.1.2. Load "Processing Toolbox" plug-in */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
===== 2.1.1. Install uDig SW =====
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

===== 2.1.2. Load "Processing Toolbox" plug-in =====
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.<br />
<b>*Name:</b> Processing Toolbox for uDig<br />
<b>*URL:</b> http://www.mangosystem.com:8080/s2toolbox_updates<br />
</div>
Now, lets’ load the Processing Toolbox into uDig.<br />
<b>Step1.</b> Set a location of repository for Processing Toolbox plug-in.<br />
[Help] --> [Find and Install] (Figure2): Install/Update window will pop up (Figure3) --> Click ‘Search for new features to install’ --> ‘Next’ button: Install window will pop up (Figure 4) --> Click ‘New Remote Site’ button à put repository Name and URL --> Click ‘OK’ button (Figure 5) --> Next button (Figure 6)

<b>Step 2.</b> Agree Feature License (Figure 7) <br />
<b>Step 3.</b> Loading plug-in (Figure 8) à Install all (Figure 9) à Restart (Figure 10)<br />
<b>Step 4.</b> View Processing Toolbox on uDig (Figure11- Figure 13)<br />

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:55:52Z

Wiki-Somakang: /* 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
===== 2.1.1. Install uDig SW =====
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

===== 2.1.2. Load "Processing Toolbox" plug-in =====
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.<br />
Name: Processing Toolbox for uDig<br />
URL: http://www.mangosystem.com:8080/s2toolbox_updates<br />
</div>
Now, lets’ load the Processing Toolbox into uDig.<br />
<b>Step1.</b> Set a location of repository for Processing Toolbox plug-in.<br />
[Help] --> [Find and Install] (Figure2): Install/Update window will pop up (Figure3) --> Click ‘Search for new features to install’ --> ‘Next’ button: Install window will pop up (Figure 4) --> Click ‘New Remote Site’ button à put repository Name and URL --> Click ‘OK’ button (Figure 5) --> Next button (Figure 6)

<b>Step 2.</b> Agree Feature License (Figure 7) <br />
<b>Step 3.</b> Loading plug-in (Figure 8) à Install all (Figure 9) à Restart (Figure 10)<br />
<b>Step 4.</b> View Processing Toolbox on uDig (Figure11- Figure 13)<br />

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:53:31Z

Wiki-Somakang: /* 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===

<p><big><b> 2.1.1. Install uDig SW </b></big></p>
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

<p><big><b> 2.1.2. Load "Processing Toolbox" plug-in</b></big></p>
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.<br />
Name: Processing Toolbox for uDig<br />
URL: http://www.mangosystem.com:8080/s2toolbox_updates<br />
</div>
Now, lets’ load the Processing Toolbox into uDig.<br />
<b>Step1.</b> Set a location of repository for Processing Toolbox plug-in.<br />
[Help] --> [Find and Install] (Figure2): Install/Update window will pop up (Figure3) --> Click ‘Search for new features to install’ --> ‘Next’ button: Install window will pop up (Figure 4) --> Click ‘New Remote Site’ button à put repository Name and URL --> Click ‘OK’ button (Figure 5) --> Next button (Figure 6)

<b>Step 2.</b> Agree Feature License (Figure 7) <br />
<b>Step 3.</b> Loading plug-in (Figure 8) à Install all (Figure 9) à Restart (Figure 10)<br />
<b>Step 4.</b> View Processing Toolbox on uDig (Figure11- Figure 13)<br />

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:51:22Z

Wiki-Somakang: /* 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===

<p><big><b> 2.1.1. Install uDig SW </b></big></p>
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

<p><big><b> 2.1.2. Load "Processing Toolbox" plug-in</b></big></p>
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.<br />
Name: Processing Toolbox for uDig<br />
URL: http://www.mangosystem.com:8080/s2toolbox_updates<br />
</div>

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:50:40Z

Wiki-Somakang: /* 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===

<p><big><b> 2.1.1. Install uDig SW </b></big></p>
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

<p><big><b> 2.1.2. Load "Processing Toolbox" plug-in</b></big></p>
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.
Name: Processing Toolbox for uDig
URL: http://www.mangosystem.com:8080/s2toolbox_updates
</div>

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:49:50Z

Wiki-Somakang: /* 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===

<p><big><b><span style='color:#0070C0'> A. Install uDig SW </span></b></big></p>
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

<p><big><b><span style='color:#0070C0'> B. Load "Processing Toolbox" plug-in</span></b></big></p>
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.
Name: Processing Toolbox for uDig
URL: http://www.mangosystem.com:8080/s2toolbox_updates
</div>

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:49:23Z

Wiki-Somakang: /* 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===

<p><big><b><span style='color:#0070C0'> A. Install uDig SW </span></b></big></p>
<div class="paragraph">
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].
</div>

<p><big><b><span style='color:#0070C0'> Load "Processing Toolbox" plug-in</span></b></big></p>
<div class="paragraph">
Please keep the repository information for Processing Toolbox plug-in.
Name: Processing Toolbox for uDig
URL: http://www.mangosystem.com:8080/s2toolbox_updates
</div>

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:46:07Z

Wiki-Somakang: /* 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
<p><big><span style='color:#0070C0'> Install uDig SW </span></big></p>
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

<p><big><span style='color:#0070C0'> load "Processing Toolbox" plug-in</span></big></p>
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:44:25Z

Wiki-Somakang: /* 2.1.2 load "Processing Toolbox" plug-in */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
<big> Install uDig SW</big>
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

<big><sup>load "Processing Toolbox" plug-in</sup></big>
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:41:38Z

Wiki-Somakang: /* 2.1.1 Install uDig SW */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
<big> Install uDig SW</big>
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:40:36Z

Wiki-Somakang: /* 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:39:51Z

Wiki-Somakang: /* 2.4 Clip dataset for the next analytic process */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.5 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:39:33Z

Wiki-Somakang: /* 2.3 Set Coordinate Reference System of the dataset */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.4 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.4 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:38:48Z

Wiki-Somakang: /* 2.1 Dataset Download */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.2 Download a dataset for geo-analysis ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.3 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.4 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:38:09Z

Wiki-Somakang: /* 2.2. Set UDig */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.1 Dataset Download ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.3. Set UDig : New Project and New Map ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.3 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.4 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:35:06Z

Wiki-Somakang: /* 2.1.1 Install uDig SW */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''].
Other uDig versions are accessible at [http://udig.refractions.net/ '''uDig webpage''' ].

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.1 Dataset Download ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.2. Set UDig ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.3 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.4 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:34:01Z

Wiki-Somakang: /* 2. Preparation */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe].
Other uDig versions are accessible at uDig webpage [http://udig.refractions.net/].

You can download uDig for Windows 64bit at [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe'''udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe''']

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.1 Dataset Download ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.2. Set UDig ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.3 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.4 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
</div>
</div>

Training Material for UN Open GIS Spiral 3

2018-12-11T08:32:23Z

Wiki-Somakang: /* 2.1.1 Install uDig SW */

== 1. General Info==
The OSGeo UN Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. Following a meeting between OSGeo Board of Directors and the UN GIS team at FOSS4G in Seoul, Korea in September 2015, the Committee has mainly worked on the UN Open GIS Initiative, a project “...to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organisations, academia, NGOs, private sector. The strategic approach shall be developed with best and shared principles, standards and ownership in a prioritized manner that addresses capability gaps and needs without duplicating efforts of other Member States or entities. The UN Open GIS Initiative strategy shall collaboratively and cooperatively develop, validate, assess, migrate and implement sound technical capabilities with all the appropriate documentation and training that in the end provides a united effort to improve the effectiveness and efficiency of utilizing Open Source GIS around the world.” (more details at [https://wiki.osgeo.org/wiki/UnitedNations_Committee]).

OSGeo UN Commiittee called proposals for developing open geospatial educational materials (more details at [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/]) as a part of the activities in the OSGeo UN Commiittee. Silvia Franceschi (HydroloGIS) was selected as a winner for "Educational Challenge 2". This document is the result of the challenge 2.

=== 1.1 Purpose of this document===
This educational material is designed as a step-by-step software learning guide for geo-analytic library called "uDig Processing Toolbox".
<div class="paragraph">
Geo-analytic functions in the 'Processing Toolbox' library are divided into <span style='color:#0070C0'> 4 categories. </span> First<span style='color:#0070C0'> General Tools </span>are to support I/O, visualize, primitive geometry functions such as extract, clip, aggregate and dissolve. Second, <span style='color:#0070C0'>Spatial Statistics Tools</span> are to provide geo-statistical analysis functions such as Ordinary Least Squares s(OLS). Third, <span style='color:#0070C0'>Raster Tools </span>are to support raster data analysis functions such as Radial Line of Sight.
</div>
<div class="paragraph">
This tutorial contains the description of the usage of some commands for environmental analysis of raster and vector data with the uDig Processing Toolbox. The purpose of this quick start document is to introduce the user in the use of the algorithms contained in the Processing Toolbox of uDig for environmental analysis in particular related to ecology and ecosystems identification.
</div>

<div class="paragraph">
In this tutorial, you will perform the following tasks:
</div>

<div class="ulist">
<ul>
<li><p>preliminary operations</p></li>
<li><p>raster data analysis</p>
<div class="ulist">
<ul>
<li><p>NDVI</p></li>
<li><p>DTM and DTM derived data</p></li>
</ul>
</div>
</li>

<li><p>vector data analysis</p>
<div class="ulist">
<ul>
<li><p>density</p></li>
<li><p>proximity analysis</p></li>
<li><p>assign attributes</p></li>
<li><p>interpolation on raster</p></li>
</ul>
</div>
</li>
</ul>
</div>

=== 1.2 Target Audience===
The primary target audience is professionals who needs geo-statistic functions.

=== 1.3 License===
This educational material was written by Silvia Franceschi and Andrea Antonello (HydroloGIS) with the menthorship of HaeKyong Kang of the Korea Research Institute for Human Settlements and Minpa Lee of MangoSystem, within the project of collaboration between the OSGEO foundation and UN institute under the framework of the [https://www.osgeo.org/foundation-news/osgeo-un-committee-educational-challenge/ UN OSGeo Challenge].
It is distributed according to the CREATIVE COMMONS deed: Attribution - NoDerivs 2.0.
According to this license type you are free to:

* copy, distribute, display and perform the work
* make commercial use of the work

Under the following conditions:

* you must attribute the work in the manner specified by the author or licensor
* you may not alter, transform, or build upon this work.

For any reuse or distribution, you must make clear to others the license terms of this work.
Any of these conditions can be waived if you get permission from the copyright holder.

Your fair use and other rights are in no way affected by the above. This is a human-readable summary of the Legal Code (the full license) that can be consulted at: [https://creativecommons.org/terms/ website].

== 2. Preparation ==

=== 2.1 Prepare uDig and "Processing Toolbox"(uDig plugin for geo-analysis library) ===
==== 2.1.1 Install uDig SW ====
You can download uDig for Windows 64bit at udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe [http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe].
Other uDig versions are accessible at uDig webpage [http://udig.refractions.net/].

<span class="plainlinks">[href="http://www.mangosystem.com:8080/udig/udig-2.0.0-SNAPSHOT.win32.win32.x86_64.exe uDig]</span>

==== 2.1.2 load "Processing Toolbox" plug-in ====
Step1. Install uDig SW on your system up to your OS.
Step2. Run uDig
Step3. Create a new project file

<div class="paragraph">

In the following section we show how to use functions in the Processing Toolbox of uDig using vector layers, satellite images and the DTM in tiff grid format and leading you running the further commands.
</div>
<div class="paragraph">

<div class="sect2">

=== 2.1 Dataset Download ===
First of all get (or download) the Processing Toolbox dataset at [https://we.tl/t-3Lva5z1zdB '''processing_toolbox_tutorial_dataset.zip'''] and unzip the content directly in a folder on your PC. The dataset covers an area around the city of Seoul in South Korea and contains three different type of information:
</div>
<div class="ulist">
* Landsat8 images ''LC08_L1TP_115034_20180721_20180731_01_T1.tar.gz'': unzip and untar this file to obtain a folder containing all the 11 available bands of the Landsat8 images in WGS84/UTM zone 52N coordinate system ''EPSG:32652''.
* Aster Digital Elevation map (DTM at a resolution of 20 m) ''20180814093648_947847400.zip'': unzip this file and consider the geotif in LongLat WGS84 coordinate system ''EPSG:4326''.
* Open Street Map vector dataset ''south-korea-latest-free.shp.zip'': unzip this file and consider the 18 shapefiles downloaded from the OSM website. The files are in LongLat WGS84 coordinate system ''EPSG:4326''.
</div>
<div class="paragraph">

=== 2.2. Set UDig ===
First of all you have to prepare a dedicated ''Project'' and ''Map'' in uDig. In order to obtain correct results of the processing tools it is recommended to convert all the dataset in a unique coordinate reference system. Since for the current use case the data have different coordinate reference systems, we choose to work with metric coordinate reference system UTM zone 52N, ''EPSG: 32652''.
</div>
<div class="paragraph">

Before starting with the analysis please do the following preliminary operations:
</div>
<div class="olist arabic">
# open uDig
# select the ''Catalog'' view from the available views of the main application (usually this is placed in the lower part of the main window)
# drag and drop the files of the Landsat8 images band 4 and 5, the DTM and the vector layers of ''landuse'', ''natural points'', ''roads'' and ''water ways'' from your ''File Manager'' into the Catalog view
# right click on the Landsat8 geotif and select ''Add to New Map'' or drag and drop it in the ''Layers'' view: this should open a new ''Map'' view with the coordinate reference system of the selected data source, in this case WGS84/UTM zone 52N (please take care that this is the projection of your working ''View'')
# drag and drop the other files directly in the ''Map'' view or in the ''Layers'' view to visualize them all in the map.
</div>
<div class="admonitionblock note">

{{note}} uDig automatically reprojects the layers in the projection of the ''Map'' view, but only for visualization, the data remain in the original projection.

</div>
<div id="procToolbox01_01" class="imageblock" style="text-align: center">

<div class="content">

[[File:01_new_map_view.png|01 new map view|800px|center]]

</div>
<div class="title">

Figure 1. Create the ''Map'' view starting from the layer of the Landsat8 images.

</div>

</div>
<div id="procToolbox01_02" class="imageblock" style="text-align: center">

<div class="content">

[[File:02_map_view_all.png|02 map view all|800px|center]]

</div>
<div class="title">

Figure 2. Import of the test dataset in uDig, zoom to all layers.

</div>

</div>
<div class="sect3">

=== 2.3 Set Coordinate Reference System of the dataset ===

<div class="paragraph">

Usually we use data from different sources therefore, very often the available information are on different coordinate reference systems (CRS) and on different/widen areas. To homogenize the works and assure that all the tools work perfectly it is reccommanded (at least) to reproject all the data in the same CRS and define a working area where to clip all the data.

</div>
<div class="paragraph">
'''Reproject''' reprojects the selected layer in the given CRS. There are two different versions of the tool specific for raster and vector layers available in:
</div>
<div class="ulist">

* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Utilities''' → '''Reproject'''
</div>
<div class="paragraph">
The tool requires in input:

</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reproject from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Resample Type'': default value is ''NEAREST'', other options are ''BILINEAR'' and ''CUBIC''</p></li>
<li><p>''Output Cell Size (optional)'': the size of the output raster if different from the original</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input raster map to the one specified here in case the input file misses this information</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>

</div>
<div class="admonitionblock important">

{{note}} It is important to fix the resolution of the output raster (Output Cell Size) especially with reprojection between systems using different measurement units (degree vs metric) and in any case to be sure to have squared cells in the output layer. Squared cells are mandatories if you want to use some analysis tools and in particular to use the tools of the ''HortonMachine'' library.

</div>
<div id="procToolbox01_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:05_raster_reproject.png|05 raster reproject]]
</div>
<div class="title">

Figure 3. Execution of the ''Reproject'' command for the raster of ''DTM''.

</div>
</div>
<div class="admonitionblock note">

{{note}} To open the graphical interface of the commands available in the list of the Processing Toolbox double click on the name of the tool you want to run. To run the tool click on the ''OK'' button after filling all the required input in the window. To exit the tool once executed, click on ''Cancel''. The tool will run every time you click on the ''Ok'' button.

</div>
<div class="admonitionblock note">
{{note}} The output raster will be visualized all white, use the ''Styling System'' of uDig for a better visualization.

</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''GeoTools Processes''' → '''Vector processes''' → '''Reproject'''
</div>
<div class="olist arabic">

<ol>
<li><p>''Feature'' layer: select the vector layer to reproject from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Forced CRS (optional)'': force the CRS of the input vector map to the one specified here in case the input file misses this information</p></li>
<li><p>''Target CRS'': the target CRS, you can write it in the form of ''EPSG:32652'' or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>CRS form current Map</p></li>
<li><p>CRS from layers → then select the layer</p></li>
<li><p>select CRS → open the standar uDig window where to select the CRS</p></li></ul>
</div></li>
<li><p>''Result'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="procToolbox01_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:06_vector_reproject.png|06 vector reproject]]
</div>
<div class="title">

Figure 4. Execution of the ''Reproject'' command for the vector of the ''landuse''.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please reproject using the same tool as for the ''landuse'' layer also the vector layers of:
</div>
<div class="ulist">
* gis_osm_natural_free_1
* gis_osm_waterways_free_1
* gis_osm_water_a_free_1
* gis_osm_roads_free_1
* gis_osm_landuse_a_free_1.
</div>

<div>
</div>
<b><font color="blue"> * Delete original layers after reprojecting</font></b>

<div class="paragraph">
After reprojecting all the layers you can delete the original layers from the ''Layers view''. To do this you can select all the layers or one layer at a time from the ''Layers'' view and select ''Delete'' from the context menu of the right mouse click.
</div>
<div id="procToolbox01_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:07_delete_layers.png|07 delete layers]]
</div>
<div class="title">

Figure 5. Delete some layers from the ''Layers'' view.

</div>
</div>

=== 2.4 Clip dataset for the next analytic process ===
<div class="paragraph">
'''Clip''' extracts the features of the selected layer for a defined region.
</div>
<div class="paragraph">
Before starting with the clipping we should define our working area as a polygon geometry. The standar process to do this operation in uDig is the following:
</div>
<div class="olist arabic">
<ol>

<li><p>create a new layer: '''Layer''' → '''Create'''</p></li>
<li><p>define the characteristics of the new layer:</p>
<div class="ulist">
<ul>
<li><p>''name'': area_of_interest</p></li>
<li><p>''attributes'':</p>
<div class="ulist">
<ul>
<li><p>name: String</p></li>
<li><p>geometry: Polygon</p></li>
<li><p>CRS: UTM zone 52N (EPSG: 32684)</p></li></ul>
</div></li></ul>
</div></li>
<li><p>click on ''OK'' to add the new layer to the project</p></li>
<li><p>select the editing tool to '''Create''' → '''Create Rectangle'''</p></li>
<li><p>draw a rectangle in the area around Seoul (not too big but big enough to contain some of the natural points, see the picture).</p></li></ol>

</div>
<div class="paragraph">
The following image contains an example of the ''area of interest''.
</div>
<div id="horton01_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:09_area_of_interest.png|09 area of interest]]
</div>
<div class="title">

Figure 6. Example of the layer of the ''area of interest''.

</div>

</div>
<div class="paragraph">
There is a new module in the Processing Toolbox developed to simplify this operation. In fact, the '''Geometry to Features''' tool can be used to automatically extract a polygon layer on the Map extent.
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Import''' → '''Geometry to Features'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Geometry (WKT)'': the geometry to import, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString</p></li>
<li><p>Polygon: and then select the first option ''Polygon from Map’s Extent''</p></li>
<li><p>Geometry from Layers…: select the layer or the features to use to create the new layer</p></li></ul>
</div></li>
<li><p>''CRS (optional)'': the CRS of the input geometry if different from the one of the current Map</p></li>
<li><p>''Name (optional)'': name for the features in the new layer</p></li>
<li><p>''Single Part (optional)'': boolean variable to define if it is required to split multipart geometry to single parts, default is ''No''</p></li>
<li><p>''Result Features'': the path and name of the output layer containing the new features.</p></li></ol>
</div>
<div id="horton01_15" class="imageblock" style="text-align: center">

<div class="content">
[[File:32_geom2feature.png|32 geom2feature]]
</div>
<div class="title">

Figure 7. Execution of the ''Geometry to Features'' command to extract the area of interest.

</div>

</div>
<div id="horton01_16" class="imageblock" style="text-align: center">
<div class="content">
[[File:33_geom2feature.png|33 geom2feature]]
</div>
<div class="title">

Figure 8. Example of the layer of the ''area of interest'' extracted with the command ''Geometry to Features''.

</div>
</div>
<div class="paragraph">
The Processing Toolbox contains some different versions of the '''clipping''' tool. You can visualize all of them just typing the word '''clip''' in the search box of the Processing Toolbox window.
</div>
<div id="horton01_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:08_search_clip.png|08 search clip]]
</div>
<div class="title">

Figure 9. Search for the different possibilities of clipping operations in the Processing Toolbox.

</div>
</div>
<div class="paragraph">

In particular we are interested in clipping both raster and vector layers and therefore we will use:

</div>
<div class="ulist">
* for raster layers:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Extract''' → '''Clip by Extent'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: selects the raster layer to clip from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Extent'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Current Extent of the Map</p></li>
<li><p>Full Extent of the Map</p></li>
<li><p>Layer’s Extent: selects the layer of the ''area_of_interest''</p></li></ul>
</div></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div id="horton01_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:10_raster_clip.png|10 raster clip]]
</div>
<div class="title">

Figure 10. Execution of the ''Clip by Extent'' command for the projected raster of the ''DTM''.

</div>
</div>
<div class="ulist">
* for vector layers:
</div>
<div class="paragraph text-center">
'''General Tools''' → '''Extract''' → '''Clip With Polygon Geometry'''
</div>
<div class="paragraph">
The tool requires in input:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Feature'' layer: select the vector layer to clip from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Clip Polygon Geometry (WKT)'': a reference for the boundaries of the clipping area, click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: then selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: select the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Output Features'': the path and name of the output vector layer.</p></li></ol>

</div>
<div id="horton01_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:11_clip_vector.png|11 clip vector]]
</div>
<div class="title">

Figure 11. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse''.
</div>

</div>
<div id="horton01_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:12_clip_vector.png|12 clip vector]]
</div>
<div class="title">

Figure 12. Execution of the ''Clip With Polygon Geometry'' command for the projected vector of the ''landuse'', select the geometry picker.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please clip using the same tools as used for ''DTM'' and ''landuse'', respectively for raster and vector layers, also the other following layers (take care to use the reprojected ones):
</div>
<div class="ulist">
* Landsat8 images of band 4 and 5: LC08_L1TP_116034_20160519_20170324_01_T1_B4.TIF and LC08_L1TP_116034_20160519_20170324_01_T1_B5.TIF
* osm_natural_utm
* osm_waterways_utm
* osm_water_a_utm
* osm_roads_utm.
</div>
<div class="paragraph">

After clipping all the layers you can delete the original layers from the ''Layers view''.
</div>
<div class="paragraph">
The final configuration of the application and data should be like the one in the next image.
</div>
<div id="procToolbox01_10" class="imageblock" style="text-align: center">

<div class="content">
[[File:13_preliminary_operations.png|13 preliminary operations]]
</div>
<div class="title">

Figure 13. Configuration of the uDig application after the preliminary operations.

</div>
</div>
<div class="paragraph">

'''SetNull''' sets specific values in the raster layer to assign to ''NoData''. This tool works only for raster layers and it allows the user to set the cell with certain values to ''NoData'' (not valid). Doing this, these cells will be automatically excluded from further elaborations on the raster maps like statistical analysis or during the evaluation of spatial indexes.
</div>
<div class="admonitionblock note">

{{note}} To query single values of the raster layers or to display the attributes of specific features of vector layers please use the '''info''' tool of uDig available in the ''Palette'' of the ''Map'' view.

</div>
<div class="paragraph">
To set the value of ''0.0'' of the Landsat8 images to ''NoData'' you can use the ''SetNull'' tool available in:
</div>
<div class="paragraph text-center">
'''Raster Tools''' → '''Conditional''' → '''Set Null'''
</div>
<div class="paragraph">

The tool requires in input:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of which to set the ''NoData'' values from the list of the raster layers available in the ''Map''
# ''Band index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''NoData Filert Expression'': expression used by the software to identify the ''NoData'' values in the layer, click on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it.
# ''Replace NoData (optional)'': flag to identify if the tool has to work in the standard or in the opposite way, that means replacing ''NoData'' values with a valid value
# ''New Value (optional)'': this value is required only if the ''Replace NoData'' is activated (''Yes'') and it represents the new value to assign to previous ''NoData'' values
# ''Output Raster'': the path and name of the output raster layer.
</div>
<div id="horton01_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:14_setnull.png|14 setnull]]
</div>
<div class="title">

Figure 14. Execution of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">
In our example we have to set the value ''0.0'' of the Landsat8 images to ''NoData''. This expression is very easy and can be written directly in the ''NoData Filert Expression'' as:
</div>
<div class="paragraph text-center">
'''[Value] = 0.0'''
</div>
<div class="paragraph">
In case there is the need to use more advanced expressions to identify the values of a raster map to set to ''NoData'' it is possible to use the ''Query Builder Dialog'' integrated in the Processing Toolbox just clicking on the <span class="image">[[File:00_question_mark.png|questionmark]]</span> button and select:
</div>
<div class="ulist">
* Layer: only for testing the expression directly in the ''Query Builder Dialog''
* Fields: in case of raster layers the only field available is the ''Value'', double click on the item in this section to add it to the query or type ''Value'' directly in the text field below
* Operators: select one of the available operators or directly type it in the text field below
* SQL where clause: the resulting SQL expression used by the software for filtering the values and assigning the ''NoData''.
</div>
<div class="paragraph">
The ''Query Builder Dialog'' gives also the possibility to show in the ''Values'' section a sample or all the data contained in the selected raster layer clicking on the ''Sample'', or for all values on ''All'' button and to ''Test'' the expression inserted clicking the specific button at the bottom of the window.
</div>
<div id="procToolbox01_12" class="imageblock" style="text-align: center">

<div class="content">
[[File:15_setnull.png|15 setnull]]
</div>
<div class="title">

Figure 15. The ''Query builder options'' of the ''Set Null'' command for the raster of the ''Landsat8'' images.

</div>
</div>
<div class="paragraph">

To go on with the tutorial please set the null values to zero using the same ''Set Null'' tool for both the raster layers of the Landsat8 images, band 4 and 5: LC08_L1TP_116034_T1_B4_utm_seoul.tif and LC08_L1TP_116034_T1_B5_utm_seoul.tif.
</div>
</div>
</div>
</div>
</div>
<div class="sect1">

== 3. Analysis of Landsat raster images ==

<div class="sectionbody">
<div class="paragraph">
In the field of environmental sciences lot of analysis have to be performed on raster data. In this tutorial we will consider two different kind of raster data:
</div>
<div class="olist arabic">
# satellite images (Landsat8)
# digital elevation maps (DTM) and derived products.
</div>
<div class="paragraph">
Raster data are continuous data in the format of a matrix of cells (or pixels) organized into rows and columns where each cell contains a value representing the content of the raster. The easiest way to observe the contened values is to use a right style, but if you need some more precise information you have to analyse them. The Spatial Toolbox provides useful tools for analyzing and do elaborations of raster layers.
</div>
<div class="paragraph">
'''Summary Statistics for Raster''' is a tool which prints a summary of the main statistics of the selected raster layer. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Summary Statistics for Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''.</p></li></ol>
</div>
<div id="procToolbox02_01" class="imageblock" style="text-align: center">

<div class="content">
[[File:16_summary_stats.png|16 summary stats]]
</div>

<div class="title">
Figure 16. Execution of the ''Summary Statistics for Raster''.
</div>

</div>
<div class="paragraph">

The tools evaluates the following statistics:
</div>
<div class="ulist">
* Count: number of valid cells of the raster layer
* Invalid Count: number of not valid cells or unclassified values
* Minimum: minimun value of the raster
* Maximum: maximum value of the raster
* Range: the entire range of the data content in the raster layer (max - min)
* Ranges: the available ranges the data content in the raster layer in case of an elaboration on multiple geometries
* Sum: the sum of the data content in the raster layer
* Mean: the average of the data content in the raster layer
* Variance: the variance of the data content in the raster layer
* Standard Deviation: the standard deviation of the data content in the raster layer
* Coefficient of Variance: the Relative Standard Deviation of the data content in the raster layer
* NoData: the value representing the NoData cells in the raster layer.
</div>
<div id="procToolbox02_02" class="imageblock" style="text-align: center">

<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>

<div class="title">
Figure 17. Output of the ''Summary Statistics for Raster'' on the ''Landsat8 image of Band 5''.
</div>
</div>
<div id="procToolbox02_03" class="imageblock" style="text-align: center">

<div class="content">
[[File:18_summary_stats.png|18 summary stats]]
</div>

<div class="title">
Figure 18. Output of the ''Summary Statistics for Raster'' on the ''DTM''.
</div>
</div>

<div class="paragraph">
'''Histogram Raster''' is a tool which calculates the information to be used to create a histogram of the content of the raster layer. In particular, this tool calculates and prints the number of cells of each different value in the map. These values can be used to display a histogram chart, just select and copy and paste them in a spreadsheet. It is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Descriptive Statistics'''
</div>
<div class="paragraph">
double click on the '''Histogram raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">

<ol>
<li><p>''Input Raster'' layer: select the raster layer to elaborate from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Crop Geometry (optional)'': a reference for "clipping" a custom area of the raster layer if you need to extract the information on a subset of the complete raster; click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer.</p></li></ul>
</div></li></ol>

</div>
<div id="procToolbox02_04" class="imageblock" style="text-align: center">

<div class="content">
[[File:19_histogram.png|19 histogram]]
</div>

<div class="title">
Figure 19. Execution of the ''Histogram Raster''.
</div>

</div>
<div id="procToolbox02_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:20_histogram.png|20 histogram]]
</div>

<div class="title">
Figure 20. Output of the ''Histogram Raster''.
</div>
</div>

<div id="procToolbox02_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:21_histogram.png|21 histogram]]
</div>

<div class="title">
Figure 21. Graphic output of the ''Histogram Raster''.
</div>
</div>

<div class="paragraph">
'''Raster Description''' is a tool which can be used to have a first description of the general metadata of the selected raster. The metadata visualized are: Name, Columns, Rows, Number of Bands, X-Y Cell Size, Pixel Type, Pixel Depth, NoData Value, the whole Extent and the CRS (Coordinate Reference System). This tool gives also the possibility to directly perform Summary Statistics.
</div>

<div id="procToolbox02_20" class="imageblock" style="text-align: center">
<div class="content">
[[File:37_raster_desc.png|37 raster desc]]
</div>

<div class="title">
Figure 22. Execution of the ''Raster Description''.
</div>
</div>

<div id="procToolbox02_21" class="imageblock" style="text-align: center">
<div class="content">
[[File:36_raster_desc.png|36 raster desc]]
</div>

<div class="title">
Figure 23. Output of the ''Raster Description''.
</div>

</div>
<div class="sect2">

=== 3.1. The Normalized Difference Vegetation Index ===

<div class="paragraph">
From an ecological and environmental point of view an interesting index which can be calculated from Landsat8 images is the NDVI. The '''Normalized Difference Vegetation Index''' is a simple graphical indicator that can be used to analyse remote sensing measurements and assess whether there is live green vegetation on the surface of the analysed area. The expression of the NDVI is:
</div>
<div class="paragraph text-center">
\(NDVI={\frac {(NIR-Red)}{(NIR+Red)}}\)
</div>
<div class="paragraph">
The Processing Toolbox contains a module to directly perform this index, it is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Math → NDVI'''
</div>

<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Near Infrared Band'' layer: select the raster layer containing the NIR information from the list of the raster layers available in the ''Map''
# ''Near Infrared Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Visible Red Band'' layer: select the raster layer containing the VIS red information from the list of the raster layers available in the ''Map''
# ''Red Band Index'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''
# ''Output Raster'': the path and name of the output raster layer.
</div>

<div class="paragraph">
The output raster layer will be shown with an homogenious
</div>
<div id="procToolbox02_07" class="imageblock" style="text-align: center">

<div class="content">
[[File:22_ndvi.png|22 ndvi]]
</div>
<div class="title">
Figure 24. Execution of the ''NDVI''.
</div>
</div>

<div class="paragraph">
To understand the content of the NDVI map it is recommended to do some statistical analysis on it, please run the modules for ''Descriptive Statistics'' on this map as described in the previous paragraph:
</div>
<div class="olist arabic">
# Summary Statistics for Raster
# Histogram
</div>

<div class="paragraph">
'''Reclassify Raster''' is used to reassign a value, a range of values, or a list of values in a raster to new output values. Reclassification is useful to assign each value (pixel) of a raster map to a category in a list of predefined categories. In our example NDVI values are in the range from -0.2 to 0.64, but these values are a bit complicated to understand for a wide public, so a reclassification process will be useful. From bibliography studies and without a real validation we can use, for example, the following ranges for reclassification:
</div>
{|
|+ Table 1. Values and classes used for reclassifying NDVI raster layer
!width="25%"| CLASS
!width="25%"| MAX VALUE
!width="25%"| MIN VALUE
!width="25%"| DESC
|-
| 0
| -0.5
| 0.0
| water
|-
| 1
| 0.0
| 0.05
| bare soil
|-
| 2
| 0.05
| 0.2
| other (roof, city, …)
|-
| 3
| 0.2
| 0.3
| grassland
|-
| 4
| 0.3
| 0.4
| agriculture
|-
| 5
| 0.4
| 0.7
| forest
|}

<div class="paragraph">
Reclassification is available in the section:
</div>
<div class="paragraph text-center">
'''Raster Tools → Reclass'''
</div>
<div class="paragraph">
double click on the '''Reclassify Raster''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Input Raster'' layer: select the raster layer to reclassify from the list of the raster layers available in the ''Map''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Reclass Ranges'': the ranges of the different categories in which to assign each value of the raster map; write here the list of categories and intervals or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Build expression: opens the ''Expression Builder Dialog'' where it is possible to insert a formula to assign the values to a class</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a set or to all the different values of one of its fields</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to select a vector layer and assign the values of the raster layer to a statistic extraction of the values of one of its fields</p></li></ul>
</div></li>
<li><p>''Retain Missing Values'': defines whether missing values in the reclass table maintain their value (true) or get mapped to NoData (false)</p></li>
<li><p>''Output Raster'': the path and name of the output raster layer.</p></li></ol>
</div>
<div class="paragraph">
To use the categories of the table above we can write them directly in the text field of the ''Reclass Ranges'' in the form of:
</div>
<div class="paragraph text-center">
''-0.2 0.0 0; 0.0 0.05 1; 0.05 0.2 2; 0.2 0.3 3; 0.3 0.4 4; 0.4 0.65 5''
</div>
<div id="procToolbox02_08" class="imageblock" style="text-align: center">

<div class="content">
[[File:24_reclass.png|24 reclass]]
</div>
<div class="title">
Figure 25. Execution of the ''Reclassify Raster''.
</div>
</div>

<div class="paragraph">
After reclassification the visualization of the NDVI map will be more clear and it is also easier to style it using a ''Unique Values'' color table.
</div>
<div class="paragraph">
Other bands of the Landsat8 images are interesting for an ecological point of view, before going on with the next operations please proceed to reclassify also the map of band 5 representing the NIR (Near Infra Red) which is important for ecology studies because healthy plants reflect this frequency. Usually the bright features of this band are parks and other heavily irrigated vegetation.
</div>
<div id="procToolbox02_09" class="imageblock" style="text-align: center">

<div class="content">
[[File:25_reclass.png|25 reclass]]
</div>

<div class="title">
Figure 26. NDVI map styled after reclassification.
</div>
</div>

<div class="admonitionblock tip">
{{note}} '''Legend''' of the visualized layers in uDig is available in the '''Decoration''' folder of the catalog. To add the legend to the map go in the ''Catalog View'' and scroll until ''Decoration'' item is visualized, then click on the arrow before the name to show its content. Double click on ''Legend'' to add it directly to the ''Map View''. To define a personalized style for the legend select the ''Legend'' layer form the ''Layers View'' and access the style editor <span class="image">[[File:27_style_button.png|questionmark]]</span>

</div>
<div id="procToolbox02_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:26_legend.png|26 legend]]
</div>
<div class="title">
Figure 27. Access to the ''Legend'' item from the ''Catalog View''.
</div>
</div>

<div class="paragraph">
'''Band Merge''' is an other interesting tool for analysing satellite data expecially Landsat8 images which are divided into 11 different images. Possible combination of these images can give the user interesting information about the elements on the surface. For example the combination of bands of Red, Green and Blue (RGB) is used to obtain a true color map, useful also for studying aquatic habitats. To do this we can use the ''Band Merge'' tool available in:
</div>
<div class="paragraph text-center">
'''GeoTools Processes → Raster processes'''
</div>
<div class="paragraph">
double click on the '''Band Merge''' entry. The required input parameters are:
</div>
<div class="olist arabic">
<ol>

<li><p>''Coverages'': select the input raster layers of the different bands to merge from the list of the raster layers available in the ''Map'', click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to select them from the ''Multiple Layers Selector''</p></li>
<li><p>''ROI (optional)(WKT)'': optional value of the region of interest if you want to run the process on a smallest area rather than all images click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to select it:</p>
<div class="ulist">
<ul>
<li><p>Point</p></li>
<li><p>LineString: selects the boundary from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Polygon: selects the polygon from the ''area_of_interest'' Layer’s Extent</p></li>
<li><p>Geometry from Layers…: selects the layer and feature ID of the polygon to use for delimiting the new vector layer</p></li></ul>
</div></li>
<li><p>''TransformChoice (optional)'': choose the transformation to use in case of a transformation of the original input data is needed; insert the expression of the transformation here or click the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line to choose how to define it:</p>
<div class="ulist">
<ul>
<li><p>Build Expression: opens the ''Expression Builder Dialog'' to write the transformation using the available tools</p></li>
<li><p>Select Multiple Fields: opens the ''Multiple Fields Selector'' where it is possible to select the fields of a vector layer as parameters of the transformation</p></li>
<li><p>Select Statistical Fields: opens the ''Statistics Fields Selector'' where it is possible to selectthe fields of a vector layer as parameters of the transformation</p></li></ul>
</div></li>
<li><p>''Index (optional)'': the index used by the TransforChoice parameter needed only if there is a TransforChoice</p></li>
<li><p>''Result'': the path and name of the output merged raster layer.</p></li></ol>
</div>
<div id="procToolbox02_11" class="imageblock" style="text-align: center">

<div class="content">
[[File:29_merge.png|29 merge]]
</div>
<div class="title">
Figure 28. Execution of the ''Band Merge'' with the detail of the window were to select the input raster layers of the different bands, The example of the true color map.
</div>
</div>

<div class="paragraph">
Other interesting maps che be evaluated using the merging tools combining the bands:
</div>
<div class="ulist">
* bands 5,4,3 to have clearer boundaries of the water bodies and stess the difference of the vegetation types
* bands 5,6,4 which is crisper than the previous one where different vegetation types can be more clearly defined and land/water interface more clear
* bands 7,5,3 similar to the previous one but in this case the vegetation appears green
* bands 6.5.2 specific to visualize agricultural vegetation.
</div>
<div class="paragraph">
Please proceed in the elaboration of these other maps and try to define different styles of visualization and to identify the differences and the peculiarities of each single map. The following images show some results.
</div>
<div id="procToolbox02_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:28_merge.png|28 merge]]
</div>
<div class="title">
Figure 29. Visualization of the output true color map of merging bands 2,3,4.
</div>
</div>

<div id="procToolbox02_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:30_merge.png|30 merge]]
</div>
<div class="title">
Figure 30. Visualization of the output true color map of merging bands 3,4,5.
</div>
</div>

<div id="procToolbox02_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:31_merge.png|31 merge]]
</div>
<div class="title">
Figure 31. Visualization of the output true color map of merging bands 3,5,7.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
</div>
</div>

<div class="sect1">

== Analysis of the Digital Terrain Model ==
<div class="sectionbody">
<div class="paragraph">
The raster of the Digital Terrain Model (DTM) contains the values of the elevation of the terrain at the given resolution. This information can be used to perform geomorphological analysis on the terrain (slope, curvature, …) or to link the information of the elevation to other discrete data.
</div>
<div class="paragraph">
For example, it could be useful to analyse the connection between a discrete information (the land use) and the elevation or the slope of the terrain. The tool to perform this operation is the ''Zonal Statistics'' which is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Zonal Tools → Zonal Statistics'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Polygon Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Output Field (optional)'': name of the new field that will be added to the input polygon layer containing the results</p></li>
<li><p>''Value Coverage'' layer: select the raster layer containing the values for which to perform zonal statistics on the polygons, in this case the ''DTM''</p></li>
<li><p>''Band Index (optional)'': optional value of band index to use for multiple band layers, otherwise leave it at '''0'''</p></li>
<li><p>''Statistics Type (optional)'': the statistical analysis on the raster values for each polygon of the features layer, you can choose between:</p>
<div class="ulist">
<ul>
<li><p>Count</p></li>
<li><p>Sum</p></li>
<li><p>Mean</p></li>
<li><p>Minimum</p></li>
<li><p>Maximum</p></li>
<li><p>Range</p></li>
<li><p>Standard Deviation</p></li></ul>
</div></li>
<li><p>''Output Features'' layer: the path and name of the output polygon layer containing the additional field with the statistics.</p></li></ol>
</div>
<div class="admonitionblock note">
{|
| ''''
| Before proceeding with the Zonal Statistics it is recommended to set zero values of the DTM map (0.0) to null with the ''Set Null'' tool as described in the previous chapter.
|}
</div>
<div class="paragraph">
The example is performed considering the average value of elevation in each polygon as specified in the following figures.
</div>
<div id="procToolbox03_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:34_zonalstats.png|34 zonalstats]]
</div>
<div class="title">
Figure 32. Execution of the ''Zonal Statistics''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Val''' and '''Cell_Area'''.
</div>
<div id="procToolbox03_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:17_summary_stats.png|17 summary stats]]
</div>
<div class="title">
Figure 33. Output of the ''Zonal Statistics'' of the DTM on the LandUse polygons with a tematic styling considering the average elevation of the polygons.
</div>
</div>
<div class="paragraph">
To analyse the results of the zonal statistics it is possible to use a spatial correlation which can be evaluated using the Ordinary Linear Regression (OLS) considering the two variables, landuse (code) and average elevation (val) respectively as dependent and independent variables. This tool is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Spatial Relationships → Ordinary Least Squares'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''landuse'' crop on the area of interest from the list of the vector layers available in the ''Map''
# ''Dependent Variable'': select the field of the input polygon layer containing the information about the dependent variable (i.e. code)
# ''Explanatory Variable'': select the field of the input polygon layer containing the information about the explanatory variable (i.e. value)
# ''Output Features'' layer: the path and name of the output polygon layer containing the additional field of the OLS.
</div>
<div id="procToolbox03_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:38_ols.png|38 ols]]
</div>
<div class="title">
Figure 34. Execution of the ''Ordinary Least Squares''.
</div>
</div>
<div class="paragraph">
The output will be a vector layer with the same features of the input one with two additional attributes (visible in the ''Table'' view) named '''Estimated''', '''Residual''', '''StdResid '''and *StdResid2'''. As you can see from the following image the *R^2''' is very low so basically there is no linear correlation between the two variables.
</div>
<div id="procToolbox03_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:39_ols.png|39 ols]]
</div>
<div class="title">
Figure 35. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div id="procToolbox03_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:40_ols.png|40 ols]]
</div>
<div class="title">
Figure 36. Output of the ''Ordinary Least Squares'' of the elevation on the landuse.
</div>
</div>
<div class="paragraph">
It is possible to do this kind of evaluations also considering a different independent variable for example the '''slope''' of the terrain.
</div>
<div style="page-break-after: always;">
</div>
<div class="sect2">
=== 4.1. Morphological analysis on DTM ===
<div class="paragraph">
The Processing Toolbox contains some tools for basic morphological analysis on a Digital Terrain Model (DTM). Example of these tools are the slope and the curvature models which will be analysed in the following sections.
</div>
<div class="paragraph">
'''Slope''' tool identifies the slope of the terrain as the gradient, or in other words, the rate of maximum change in z-value from each cell of a raster surface following the drainage directions. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Slope'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the maximum gradients of the surface from the list of the vector layers available in the ''Map''
# ''Measurement Units (optional)'': select the unit of measurement for the output slope raster map between the given options (Degree, Percentrise)
# ''Z factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line
# ''Output Raster'' layer: the path and name of the output raster layer containing the slope.
</div>
<div id="procToolbox03_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:41_slope.png|41 slope]]
</div>
<div class="title">
Figure 37. Execution of the ''Slope''.
</div>
</div>
<div id="procToolbox03_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:42_slope.png|42 slope]]
</div>
<div class="title">
Figure 38. Output of the ''Slope'' in degree.
</div>
</div>
<div class="paragraph">
'''Curvature''' tool calculates the curvature of a raster surface (''DTM''). The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Curvature'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the curvature of the surface from the list of the vector layers available in the ''Map''
# ''Z Factor (optional)'': specify the number of ground x,y units in one surface Z unit; this value can be constant or given as field in a vector layer (you can select the vector layer and the other parameters using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Raster'' layer: the path and name of the output raster layer containing the curvature.
</div>
<div id="procToolbox03_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:43_curvature.png|43 curvature]]
</div>
<div class="title">
Figure 39. Execution of the ''Curvature''.
</div>
</div>
<div id="procToolbox03_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:44_curvature.png|44 curvature]]
</div>
<div class="title">
Figure 40. Output of the ''Curvature'' of the terrain.
</div>
</div>
<div class="paragraph">
The Processing Toolbox contains two modules to quantify the topographic heterogeneity of a surface, one general and one more specific for terrain.
</div>
<div class="paragraph">
'''Roughness''', represents the general tool calculate the roughness of the surface as the maximum difference between the values in two cells. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Roughness'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the roughness of the surface from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.
</div>
<div id="procToolbox03_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:45_roughness.png|45 roughness]]
</div>
<div class="title">
Figure 41. Execution of the ''Roughness''.
</div>
</div>
<div id="procToolbox03_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:46_roughness.png|46 roughness]]
</div>
<div class="title">
Figure 42. Output of the ''Roughness'' of the terrain as a general surface.
</div>
</div>
<div class="paragraph">
'''Roughness''', represents the tool specific to evaluate the ruggedness of the terrain (''DTM'') as the average difference in height. The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Surface Analysis → Terrain Ruggedness Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Raster'' layer: select the raster layer of the ''DTM'' for which to evaluate the ruggedness from the list of the raster layers available in the ''Map''
# ''Output Raster'' layer: the path and name of the output raster layer containing the Terrain Ruggedness Index.
</div>
<div id="procToolbox03_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:47_tri.png|47 tri]]
</div>
<div class="title">
Figure 43. Execution of the ''Terrain Ruggedness Index''.
</div>
</div>
<div id="procToolbox03_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:48_tri.png|48 tri]]
</div>
<div class="title">
Figure 44. Output of the ''Terrain Ruggedness Index'' of the terrain.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| As shown in the previous images, considering the DTM the two variables (roughness and Terrain Ruggedness Index) have different values but the same behaviour.
|}
</div>
<div class="paragraph">
It is now possible to evaluate the correlation between the ''Land Use'' and all these variables, calculated as raster maps (slope, curvature, roughness and Terrain Ruggedness Index) as previously done with the DTM using the ''Zonal Statistics'' and ''Ordinary Least Squares (OLS)'' tools.
</div>
</div>
<div class="sect2">

=== 4.2. Add information to vector layers ===
<div class="paragraph">
There is another possibility to extract continuous information over a surface from raster layers to discrete points in a vector layer.
</div>
<div class="paragraph">
'''Extract Raster Values to Points''' extracts the cell values of a raster for a set of points and stores these values in the attribute table of an output vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Calculation → Extract Raster Values to Points'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''natural sites'' for which to extract the values from the list of the vector layers available in the ''Map''
# ''Value Field (optional)'': name of the field containing the values of the raster layer in the new vector layer
# ''Value Raster'' layer: select the raster layer (i.e. the Terrain Ruggedness Index, Slope) of from which to extract the values to add to the vector layer from the list of the raster layers available in the ''Map''
# ''Extraction Type (optional)'': select the value to extract from the raster layer; the options are: Default, SlopeAsDegree, SlopeAsPercentrise, Aspect
# ''Output Features'' layer: the path and name of the output vector layer containing the additional field with raster values.
</div>
<div id="procToolbox03_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:49_extract_rast2point.png|49 extract rast2point]]
</div>
<div class="title">
Figure 45. Execution of the ''Extract Raster Values to Points''.
</div>
</div>
<div id="procToolbox03_15" class="imageblock" style="text-align: center">
<div class="content">
[[File:50_extract_rast2point.png|50 extract rast2point]]
</div>
<div class="title">
Figure 46. Output of the ''Extract Raster Values to Points''.
</div>
</div>
</div>
</div>
</div>

<div class="sect1">

== Working with vector data ==
<div class="sectionbody">
<div class="paragraph">
Geospatial vector layers are a representation of the world using points, lines, and polygons. Vector models usually are used for storing data that has discrete boundaries stored in an attribute table. The attribute table is definitely a table containing for each feature the values of the list of attributes available, some of them can also be null or zero.
</div>
<div class="paragraph">
Analysis on vector data can be performed on geometries or on some attribute and, in general, are not so memory expensive like the rasters analysis. In this chapter we will see some of the possibilities available in the Processing Toolbox.
</div>
<div class="sect2">
=== 5.1. Analysis of single layers ===
<div class="paragraph">
The '''Nearest Neighbor Index (NNI)''' is based on the average distance from each feature to its nearest neighboring feature. It measures the spatial distribution of a pattern to evaluate if it is regularly dispersed (=probably planned), randomly dispersed, or clustered. It is normally used for spatial geography (study of landscapes, human settlements, etc).
</div>
<div class="paragraph">
The NNI is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution:
</div>
<div class="ulist">
* NNI < 1 : the pattern exhibits clustering
* NNI = 1 : randomly dispersed pattern
* NNI > 1 : the trend of the distribution is toward dispersion or competition
* NNI = 2.15 : regularly dispersed /uniform pattern.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Nearest Neighbor Index'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to evaluate the NNI from the list of the vector layers available in the ''Map''
# ''Distance Method (optional)'': method to evaluate the distance between the single features and each neighboring feature, the available options are ''Euclidean'' and ''Manhattan''
# ''Area (optional)'': the area of the study region (you can select the vector layer to use to evaluate the area using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div id="procToolbox04_01" class="imageblock" style="text-align: center">
<div class="content">
[[File:51_nni.png|51 nni]]
</div>
<div class="title">
Figure 47. Execution of the ''Nearest Neighbor Index''.
</div>
</div>
<div class="paragraph">
The Z score value is a measure of statistical significance to evaluate whether or not to reject the null hypothesis (in this case, randomly distributed points). If an area value is not specified, then the area of the minimum enclosing rectangle around all the features is used. The result is a report containing the NNI of the elements in the input layer over the specified area. The variables reported are:
</div>
<div class="ulist">
* Observed Point Count
* Study Area
* Observed Mean Distance
* Expected Mean Distance
* Nearest Neighbor Index
* Z-Score
* p-Value
* Standard Error
</div>
<div id="procToolbox04_02" class="imageblock" style="text-align: center">
<div class="content">
[[File:52_nni.png|52 nni]]
</div>
<div class="title">
Figure 48. Output of the ''Nearest Neighbor Index'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
In this case the Z-Score shows that there is not statistical significance in this evaluation, even if the NNI 0.3 means that the distribution exhibits some clusters.
</div>
<div class="paragraph">
Other methods to perform point pattern analysis is the ''quadrant method'' using the '''Quadrant Analysis''' tool. This technique consists in dividing the study area into sub-regions (aka quadrats). Then, the point density is computed for each quadrat by dividing the number of points in each quadrant by the quadrant’s area. The version integrated in the Processing Toolbox consider only squares quadrants. The module is available in:
</div>
<div class="paragraph text-center">
'''Spatial Statistics → Point Pattern Analysis → Quadrant Analysis'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the quadrant analysis from the list of the vector layers available in the ''Map''
# ''Grid Size (optional)'': the dimension of the quadrants in which to divide the area of the study region (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line).
</div>
<div class="admonitionblock note">
{|
| ''''
| The quadrant size influence the measure of local density and must be chosen with care. If the quadrants size is too small there is the risk of having many quadrants with no points which may prove uninformative. In case of too large quadrants size there is the risk of missing particular changes in spatial density distributions. An other peculiarity of this method is that the quadrant regions do not have to take on a uniform pattern across the study area.
|}
</div>
<div id="procToolbox04_03" class="imageblock" style="text-align: center">
<div class="content">
[[File:53_quadrant.png|53 quadrant]]
</div>
<div class="title">
Figure 49. Execution of the ''Quadrant Analysis''.
</div>
</div>
<div id="procToolbox04_04" class="imageblock" style="text-align: center">
<div class="content">
[[File:54_quadrant.png|54 quadrant]]
</div>
<div class="title">
Figure 50. Output of the ''Quadrant Analysis'' of the ''Natural Points''.
</div>
</div>
<div class="paragraph">
'''Kernel Density''' extend the quadrant methodology, like the quadrant density, it computes a localized density for subsets of the study area, but unlike the quadrant density, the sub-regions overlap one another providing a moving sub-region window. This moving window is defined by a kernel. In this way, the kernel density approach generates a grid of density values based on cell size smaller than the kernel window. Each cell is assigned the density value computed for the kernel window centered on that cell. The output is a raster containing the density values.
</div>
<div class="paragraph">
The kernel defines the shape and size of the window, but it can also weight the points following a defined kernel function. The most popular kernel functions assign weights to points that are inversely proportional to their distances to the kernel window center. The simplest of functions is a basic kernel where each point in the kernel window is assigned equal weight.
</div>
<div class="paragraph">
The module is available in:
</div>
<div class="paragraph text-center">
'''Raster Tools → Density → Kernel Density'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
<ol>
<li><p>''Point Features'' layer: select the vector layer of the ''Natural Points'' for which to perform the kernel density from the list of the vector layers available in the ''Map''</p></li>
<li><p>''Kernel Function (optional)'': the function to use to weight the points in the kernel</p></li>
<li><p>''Population Field (optional)'': the field containing the population value for each feature, if available</p></li>
<li><p>''Search Value (optional)'': the radius of the kernel used to calculate the density (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Cell Size (optional)'': the value of the cell size of the output raster (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)</p></li>
<li><p>''Output Extent (optional)'': the region of the output raster (specify the boundaries), you can select the options available to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line:</p>
<div class="ulist">
<ul>
<li><p>''Current Extent of the Map''</p></li>
<li><p>''Full Extent of the Map''</p></li>
<li><p>''Layers Extent'': select the raster or vector layer from the list of all the layers available in the ''Map''</p></li>
<li><p>''Output Raster'' layer: the path and name of the output raster layer containing the roughness of the surface.</p></li></ul>
</div></li></ol>
</div>
<div id="procToolbox04_05" class="imageblock" style="text-align: center">
<div class="content">
[[File:55_kernel_density.png|55 kernel density]]
</div>
<div class="title">
Figure 51. Execution of the ''Kernel Density''.
</div>
</div>
<div id="procToolbox04_06" class="imageblock" style="text-align: center">
<div class="content">
[[File:56_kernel_density.png|56 kernel density]]
</div>
<div class="title">
Figure 52. Output of the ''Kernel Density'' of the ''Natural Points''.
</div>
</div>
<div class="admonitionblock warning">
{|
| ''''
| This elaboration uses much memory and it requires lot of time to finish. Please be careful of delimiting the extent of the elaboration and a reasonable value for the output cell size.
|}
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.2. Combination of multiple layers ===
<div class="paragraph">
In environmental studies it is often useful to perform analysis on multiple layers to understand if there is a correlation between different discrete information. An example of this is the evaluation of the distance between the features in a layer with the nearing neighboring features in a second layer. '''Calculate Nearest Neighbor Distance''' calculates the distance between each feature in the input layer and the closer feature in a second layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Proximity Analysis → Calculate Nearest Neighbor Distance'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Features'' layer: select the vector layer of the ''Natural Points'' for which to calculate the distance from the list of the vector layers available in the ''Map''
# ''Near Features'' layer: select the vector layer of the ''Roads'' or ''Water Lines'' to use as reference to calculate the distance from the features of the ''Input Layer'', from the list of the vector layers available in the ''Map''
# ''Near ID Field (optional)'': the field containing the ID of the nearest feature (output layer)
# ''Maximum distance (optional)'': the value of the maximum distance to explore for searching the feature (you can select the vector layer to use to define this value using the <span class="image">[[File:00_question_mark.png|questionmark]]</span> at the end of the line)
# ''Output Features'' layer: the path and name of the output vector layer containing the proximity information for each feature of the ''Input Features'' layer.
</div>
<div id="procToolbox04_050" class="imageblock" style="text-align: center">
<div class="content">
[[File:57_distance.png|57 distance]]
</div>
<div class="title">
Figure 53. Execution of the ''Calculate Nearest Neighbor Distance'' vs the ''Roads''.
</div>
</div>
<div id="procToolbox04_060" class="imageblock" style="text-align: center">
<div class="content">
[[File:58_distance.png|58 distance]]
</div>
<div class="title">
Figure 54. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Natural Points'' vs the ''Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| The output of the Nearest Neighbor Distance tool shows clearly that the closest road to the natural points are ''footways''.
|}
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''. The result is the following:
</div>
<div id="procToolbox04_07" class="imageblock" style="text-align: center">
<div class="content">
[[File:59_distance.png|59 distance]]
</div>
<div class="title">
Figure 55. Output of the ''Calculate Nearest Neighbor Distance'' of the ''Water Lines'' vs the ''Roads''.
</div>
</div>
<div style="page-break-after: always;">
</div>
</div>
<div class="sect2">

=== 5.3. Summary of statistics on vector layers ===
<div class="paragraph">
The Processing Toolbox contains a set of tools which can be used to create a statistics report on the results obtained for the different analysis. In this example we can use some tools to realize charts on the distance calculated between the ''Natural Points'' and the ''Roads'' or the ''Water Lines''.
</div>
<div class="paragraph">
'''Histogram''' is a tool to create a histogram chart on a defined field of the selected vector layer. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Histogram'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the histogram from the list of the vector layers available in the ''Map''
# ''Input Field'': select the field of the vector layer to use as reference for the chart from the list of the layers attributes (only numeric attributes are considered)
# ''Bin Size'': the number of bins in which to divide the range of the values in the input field
# ''Y Axis Type'': select if you want the values of the ''Ratio'' or the ''Frequency'' of the values in the ''Y'' axis.
</div>
<div id="procToolbox04_08" class="imageblock" style="text-align: center">
<div class="content">
[[File:60_histogram.png|60 histogram]]
</div>
<div class="title">
Figure 56. Execution of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_09" class="imageblock" style="text-align: center">
<div class="content">
[[File:61_histogram.png|61 histogram]]
</div>
<div class="title">
Figure 57. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div id="procToolbox04_10" class="imageblock" style="text-align: center">
<div class="content">
[[File:62_histogram.png|62 histogram]]
</div>
<div class="title">
Figure 58. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Roads''.
</div>
</div>
<div class="paragraph">
Now it is possible to use the same tool to perform the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
<div id="procToolbox04_11" class="imageblock" style="text-align: center">
<div class="content">
[[File:63_histogram.png|63 histogram]]
</div>
<div class="title">
Figure 59. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div id="procToolbox04_12" class="imageblock" style="text-align: center">
<div class="content">
[[File:64_histogram.png|64 histogram]]
</div>
<div class="title">
Figure 60. Output of the ''Histogram'' on the distance between the ''Natural Points'' and the ''Water Lines''.
</div>
</div>
<div class="paragraph">
'''Scattered Plot''' is a tool to create a scattered plot chart on a defined field of the selected vector layer using an other field as reference variable. The module is available in:
</div>
<div class="paragraph text-center">
'''General Tools → Graph → Scattered Plot'''
</div>
<div class="paragraph">
The required input parameters are:
</div>
<div class="olist arabic">
# ''Input Layer'': select the vector layer of the ''Natural Points with road distance'' for which to create the scattered plot from the list of the vector layers available in the ''Map''
# ''Independent Var Field (X Axis)'': select the field of the input vector layer to use as independent variable on the ''X'' axis (only numeric fields can be accepted)
# ''Dependent Var Field (X Axis)'': select the field of the input vector layer to use as dependent variable on the ''Y'' axis (only numeric fields can be accepted)
# ''Calculate Basic Statistics'': select this chechbox to extract also the basic statistics information in the same process
# ''Calculate Pearson Correlation Coefficient'': select this chechbox to extract also the information related to the Pearson Correlation Coefficient in the same process.
</div>
<div id="procToolbox04_13" class="imageblock" style="text-align: center">
<div class="content">
[[File:65_histogram.png|65 histogram]]
</div>
<div class="title">
Figure 61. Execution of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div id="procToolbox04_14" class="imageblock" style="text-align: center">
<div class="content">
[[File:66_histogram.png|66 histogram]]
</div>
<div class="title">
Figure 62. Output of the ''Scattered Plot'' on the distance between the ''Natural Points and the _Roads''.
</div>
</div>
<div class="admonitionblock note">
{|
| ''''
| the ''Independent Variable, X'' in this case is the code representing the category of the road.
|}
</div>
</div>
</div>
</div>
</div>
<div id="footer">
<div id="footer-text">
Version 0.1<br />
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