Difference between revisions of "20191000-QGIS-US"

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Dennis McKay - Visualizing the Uncertainty of Parcel Boundary Locations - Some parcel boundaries are depicted in locations incongruous with the underlying remotely-sensed data. This discrepancy confounds critical land-related determinations.  A user is faced with not the being able to make an informed decision until the datasets are resolved to an acceptable tolerance. While determining which dataset is positionally inaccurate it is important to realize that raster data uncertainty is generally consistent throughout the dataset.  The uncertainty of parcel corner locations (if properly derived from the analysis of survey measurements using parametric least squares analysis) is different for every point.  Strategies to visualize the expected uncertainty of parcel location would help end users to determine whether parcel vectors or underlying raster data needs improving.  Openly publishing a standardized geodatabase of survey measurements as well as established network analysis/adjustment tools would usher in a future where parcel locations would evolve toward certainty.  The use of visualizations such as augmented reality and virtual reality would assist data producers and data consumers in comprehending positional uncertainty and determining the appropriateness of a dataset in making critical decisions.
 
Dennis McKay - Visualizing the Uncertainty of Parcel Boundary Locations - Some parcel boundaries are depicted in locations incongruous with the underlying remotely-sensed data. This discrepancy confounds critical land-related determinations.  A user is faced with not the being able to make an informed decision until the datasets are resolved to an acceptable tolerance. While determining which dataset is positionally inaccurate it is important to realize that raster data uncertainty is generally consistent throughout the dataset.  The uncertainty of parcel corner locations (if properly derived from the analysis of survey measurements using parametric least squares analysis) is different for every point.  Strategies to visualize the expected uncertainty of parcel location would help end users to determine whether parcel vectors or underlying raster data needs improving.  Openly publishing a standardized geodatabase of survey measurements as well as established network analysis/adjustment tools would usher in a future where parcel locations would evolve toward certainty.  The use of visualizations such as augmented reality and virtual reality would assist data producers and data consumers in comprehending positional uncertainty and determining the appropriateness of a dataset in making critical decisions.
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Becky Wilkes - The SQUAD Tool - I have worked for the past decade in global public health, on a large contract that oversees the strengthening of health information systems in countries often overwhelmed by health burdens such as HIV, tuberculosis, and malaria.  Many of these countries, such as Nigeria, Kenya and Tanzania, have only recently developed country Master Facility Lists that contain basic information, such as name, type, size, and location of all of the many thousands of health facilities in their countries.  These databases are not always accurate, so my team recently developed a tool to help health analysts who are not typically GIS experts to assess and improve this data, by looking for the presence of certain anomalies in the data with a plugin tool.
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The Spatial Quality Anomalies Diagnosis (SQUAD) Tool can rapidly and systematically identify the presence of any of these anomalies in each record in a Master Facility List (MFL), which can then be investigated further to determine      whether there is a data quality issue, as an aid to improving the overall quality of the MFL. I will share information on how the tool was developed and how it has been used, particularly by the US Department of State and by the Ministry of Health of Nigeria.
  
 
==Sponsors==
 
==Sponsors==

Revision as of 13:00, 22 October 2019

Date

October 25th 2019

Description

A QGIS Centric Meeting will be held on October 25th 2019 in Chattanooga TN at Chattanooga State.

We have a maximum capacity of 135 people at the moment. This can change if it fills up early.

We are seeking presentations centered around QGIS. For now email rjhale@northrivergeographic.com

Time

8:30 EST to 4:30 EST

Location

Chattanooga State Technical Community College

Allbright Omniplex Building

4501 Amnicola Highway

Chattanooga TN 37406

Tickets

Tickets are $25

If you want to sponsor the meeting you have two options:

  • $50 for Silver Sponsorship. That gets you one free ticket in plus help defray some of the cost.
  • $100 for Gold Sponsorship. That gets you two free tickets and helps defray some of the costs.

If you can't afford a ticket contact me (rjhale@northrivergeographic.com) and We will work on a scholarship!

Registration

https://www.eventbrite.com/e/qgis-conference-tickets-67208884583

Food

I have hopefully put something on the tickets but if you have any dietary restrictions please let me know and we will get it handled. Food is provided at this event and I'd prefer to not kill/cause gastric distress to you.

Submit

We are seeking presentations centered around QGIS:

  • Are you using QGIS for work related activities?
  • Programming with QGIS?
  • QGIS in Humanitarian Functions?
  • QGIS with Databases?
  • Government Agency using QGIS?

Social

http://www.taphousechatt.com/

October 24th 2019

Presentations

Keynote: Nyall Dawson - Nyall has been a core developer with the QGIS project since 2013. During this time he has contributed over 5000 commits to the project, and today is one of the most active developers on the project. Nyall's contributions to QGIS cover a wide range of areas - from improvements to the map rendering and symbology engines, enhancements to labeling and print layout functionality, right through to optimisations of the underlying spatial processing algorithms utilised by QGIS. He is dedicated to making QGIS a unique tool capable of creating cartographic effects which to date have not been available in GIS software applications. Nyall is currently the proprietor and lead developer at North Road Consulting, an Australian spatial development consultancy which predominantly focus on investing in and promoting use of open source GIS applications.

Randal Hale - QGIS: It's all about Form(s) - QGIS comes with the ability to create forms to help you input data or capture data. You can build simple forms to help users avoid misspellings and help speed up data capture. You can also build forms where data entry is dependent on previous data entered as well as forms where data entry depends on other GIS data. Building Forms in QGIS is easy, powerful, and easily done if you have no programming experience. I'm going to attempt to talk you through the easiest to make forms plus one difficult form to show you how easy this can be (or hard depending on how the demos work).

Chad Howard - Using QGIS with TN's 911 Database Standard - Henry County 911 recently moved away form their COTS system and started using QGIS, PostGIS, and Fulcrum to collect and maintain the county's 911 data. This talk covers some of the in's and out's of switching software, tools, and workflows.

Erich Purpur - EcoValuator: QGIS plugin development. Working in collaboration with Key-Log Economics (An environmental economics consulting firm) in a project funded by the National Fish & Wildlife Foundation, I (Erich Purpur) worked with a group of other developers and contributors to build EcoValuator, a plugin built for QGIS 3. EcoValuator is built on python and provides a simple means of estimating the dollar value of a study area, based on the land cover types in that study area, and on your ecosystem service of choice. This presentation will cover background information about the project, what are ecosystem services, how the EcoValuator works, challenges of using the QGIS python API, and demonstration of the plugin in action.

Bernie Drahola - Building a cloud-based mapping and analysis solution based on Openlayers and CesiumJS. 18 month ago our team felt the need for having a next Gen cloud mapping solution. We did not want to leave it all to ArcGIS Online, so we decided to build our own. It is designed to make maps, analyze data, add custom database solutions, and to share maps and data with fellow users.Take a look behind the scene of the journey of putting it all together and learn how far we have come and what are our ideas in terms of connecting Open Source solutions like QGIS and GeoServer.

Jody Garnett - GeoCat Bridge for QGIS - We would like to share one of the most effective publishing solutions for QGIS - the new GeoCat Bridge for QGIS. This desktop first approach to a hybrid infrastructure provides a great “one-click” publication workflow:

  • QGIS layer identification information to register published dataset in online catalog
  • Publish layers using GeoServer or MapServer (with more options planned)
  • Great cartography support adapting desktop styling to a range of format
  • GeoCat Bridge was previously known for helping ArcMap users publish data, metadata and importantly cartography to a GeoServer or MapServer stack. With GeoCat Bridge 4, and customer demand, we are pleased to bring this experience to QGIS Desktop. This presentation looks into what the qgis-bridge-plugin offers, functionality made available for the processing toolbox, and the open source python libraries used to make it all happen. GeoCat is an established open-source company focused on helping government customers of all sizes make the best use of open source. Our company is known as experts with spatial-data-infrastructure, core contributors of GeoNetwork, and supporting OSGeo community on behalf of our customers.

Keith Jenkins - Supporting QGIS at an Academic (Cornell University) Library - Over the years, QGIS has become our tool of choice when assisting student, staff, and faculty researchers at our library's busy GIS Help Desk. We'll discuss some of our favorite and most commonly-used QGIS features, and why we prefer to teach QGIS to those who are new to GIS. We support other GIS software as well, but increasingly come across cases where the equivalent QGIS workflow is so much simpler or faster that we would be remiss not to share it and thereby gain a new QGIS advocate.

Doug Newcomb - Quick methods for recreating a DEM when reprojecting a LiDAR point Cloud - Working with multiple LiDAR collection point clouds across a landscape can require reprojecting the point cloud and rebuilding a DEM for further analysis. It's fairly straightforward to create a DEM from ground points, but there will be holes for buildings and waterbodies where breaklines may not be present to assist in filling in the holes. Using the LiDAR ground point data, it's possible to quickly fill voids using GRASS GIS raster methods, and to identify areas where the technique does not work well and further work is needed.

Dennis McKay - Visualizing the Uncertainty of Parcel Boundary Locations - Some parcel boundaries are depicted in locations incongruous with the underlying remotely-sensed data. This discrepancy confounds critical land-related determinations. A user is faced with not the being able to make an informed decision until the datasets are resolved to an acceptable tolerance. While determining which dataset is positionally inaccurate it is important to realize that raster data uncertainty is generally consistent throughout the dataset. The uncertainty of parcel corner locations (if properly derived from the analysis of survey measurements using parametric least squares analysis) is different for every point. Strategies to visualize the expected uncertainty of parcel location would help end users to determine whether parcel vectors or underlying raster data needs improving. Openly publishing a standardized geodatabase of survey measurements as well as established network analysis/adjustment tools would usher in a future where parcel locations would evolve toward certainty. The use of visualizations such as augmented reality and virtual reality would assist data producers and data consumers in comprehending positional uncertainty and determining the appropriateness of a dataset in making critical decisions.

Becky Wilkes - The SQUAD Tool - I have worked for the past decade in global public health, on a large contract that oversees the strengthening of health information systems in countries often overwhelmed by health burdens such as HIV, tuberculosis, and malaria. Many of these countries, such as Nigeria, Kenya and Tanzania, have only recently developed country Master Facility Lists that contain basic information, such as name, type, size, and location of all of the many thousands of health facilities in their countries. These databases are not always accurate, so my team recently developed a tool to help health analysts who are not typically GIS experts to assess and improve this data, by looking for the presence of certain anomalies in the data with a plugin tool.

The Spatial Quality Anomalies Diagnosis (SQUAD) Tool can rapidly and systematically identify the presence of any of these anomalies in each record in a Master Facility List (MFL), which can then be investigated further to determine whether there is a data quality issue, as an aid to improving the overall quality of the MFL. I will share information on how the tool was developed and how it has been used, particularly by the US Department of State and by the Ministry of Health of Nigeria.

Sponsors

North River Geographic Systems, Inc - Gold Sponsor

Tony Kinder, PE, RLS - Gold Sponsor

Wicked Moon Webs - Gold Sponsor

Adam Cox - Gold Sponsor

Carl Anderson, GISP - Gold Sponsor

Drahola Technologies - Gold Sponsor

Paul Wickman - Gold Sponsor

Julian Burke - Silver Sponsor

Chad Howard - Silver Sponsor

Jody Garnett - Silver Sponsor