Edu Data Package North Carolina

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This page is an ideas collection for a new educational/training data set. We want to create a new data set similar to the GRASS Spearfish dataset. This page is being worked on by Helena Mitasova and Markus Neteler.


NC related Data Sources


Proposed new data set North Carolina

Area in and around Wake county (eastern section of the Triangle) has public data for all basic data layers that were in Spearfish and there is an easy access to USGS data, local county data, EPA, State Climate Office, NCFlood maps and others through the above listed web sites. There is a big enough city, but also some rural areas that still have some agriculture with rolling topography . SE of it is Johnston county that has FOSS-based county GIS, running mapserver and PostGIS on-line.

Suggested region (15km x 13.5km city + rural) in stp[m]:

  • north: 228500 south: 215000 west: 630000 east: 645000
  • nsres: 30 ewres: 30 rows: 450 cols: 500

in lat/long

  • long: -78.77428134 lat: 35.80960938 (north/west corner)
  • long: -78.60830318 lat: 35.80918894 (north/east corner)
  • long: -78.60889171 lat: 35.68750730 (south/east corner)
  • long: -78.77462049 lat: 35.68792712 (south/west corner)

previous suggestion (larger region - that would be too much data)

  • LL(SW) corner: -78.7854 (78:47:06), 35.5897 (35:35:23)
  • UR(NE) corner: -78.4466 (78:26:46), 35.8689 (35:52:08)

For DEFAULT region we use entire NC (slightly beyond) to accomodate various subregions for thematic data sets (e.g. coast, mountains, urban)

  • LL(SW) corner: -85.0000, 33.0000
  • UR(NE) corner: -75.0000, 37.0000


Coordinate systems:

  • Geographic Coordinate System in decimal degrees WGS84 horizontal datum (close to NAD83 but there are submeter differences). This is EPSG:4326 SRS/CRS that all the OGC compliant software tends to use
  • NC State Plane Coordinate System, NAD 83 datum, units of meters: EPSG 3358
  • lot of local data and NCFlood mapping lidar come in US Survey feet (new EPSG 3404, the old wrong 3359 is deprecated)
  • xy for scanned historical maps and other non-georeferenced data

In addition to GRASS databases, the data will be provided in their original formats (shapes files, Arcgrid, tiff/tfw, etc.) and links to sites where the data can be downloaded will be provided too.

We suggest to package the data set in thematic sets (aka GRASS Mapsets concept).

The test version of GRASS LOCATION

Test version of the data set, ready to use with GRASS, is available here [1]. Some changes of map names are expected, FGDC metadata and full description will be added, but the data set can be used for testing.


The below list needs update, Ramona GIS inventory terminology http://nc.gisinventory.net/ is used in some sections

RASTER

Status: Baseline raster maps in PERMANENT

  • elevation: 30m, 10m lidar-based NED, 30m SRTM-V1, 6m NCFlood DEM, 1m lidar raster for rural subarea (Lake Wheeler farm LW)
  • landcover: LULC 1996 (1992, 1998 and 2001 will go into thematic mapset), landuse 1m for rural area
  • orthoimagery: 2001, 1m resolution tile for rural area (additional years and higher resolution will go into imagery mapset
  • landsat7

rasters derived from elevation and vector data:

  • derived from DEM:
    • slope, aspect
    • contributing area, stream network
  • derived from vector data
    • counties, zipcodes
    • soils, geology (needs labels)
    • major roads
    • hydrography - lakes (note Ramona does not use terms streams, lakes, rivers, should we?)

Additional data that can go into the basic/general data set

  • Original data:
    • elevation (NC One map USGS NED, lidar based)
    • landuse/landcover (NC One map EPA 1998, check for newer)
    • aerial images (raw stereo pair + orthophotos)
    • raw geocoded LANDSAT7 satellite data, derived vegetation indices and land surface temperatures
    • raw SRTM V2
    • DRG topo sheets
    • Historical maps, e.g. Schools situation North Carolina 1871 to 1876
    • HydroSHEDS data (check if resolution is high enough) URL, but only non-commercial use
  • Derived data (from vector maps, maybe not needed? - this should go into specialized packages - e.eg. terrain analysis, image processing):
    • DEM from Lidar vector points
    • complete set of topographic parameters (slope, aspect, different types of curvature)
    • streams from DEM
    • landforms
    • derived satellite indices
    • hydrologically conditioned SRTM V2

VECTOR

Status: Framework data layers (minimum needed to replace Spearfish) - put into PERMANENT

  • point data:
    • schools (to replace bugsites and archsites): done
    • climate stations
    • geodetic control points: done
    • bridges: done
    • geographic place names
  • line data
    • hydrography (streams)
    • roads,
    • railroads: done
    • contours
  • polygon data
    • boundaries: cities, counties: done
    • zip codes
    • parcels (to replace fields)
    • soils: done
    • building footprints

Additional data for general and specialized data sets

  • needs cleanup, can be nicely organized using Ramona GIS inventory that also shows which data layers are available for our area
  • line data:
    • railroads
    • roads (TIGER and simplified)
    • streams
  • area data:
    • countyboundaries
    • geology
    • landowners (should cover owners, fields)
    • landuse/landcover
    • parcels (land owners, fields)
    • quadrangles
    • soils
    • urban areas
    • US Census 2000 maps
    • voting districts
    • zoning districts
    • ZIP codes

Packaging issues

  • convert feet to meters if needed
  • File Naming convention
  • Metadata management (most data include standard FGDC metadata) , where to store them in GRASS?
  • provide in common GIS formats as well as GRASS location

... see Geodata Packaging Working_Group#Tasks.

Additional proposed themes for data sets

  1. Coast
  2. Urban
  3. Atmospheric 3D
  4. Hydrology and earth surface processes
  5. Vegetation, land use (image processing, multitemporal)
  6. Note, for example, the NCOne hydrography, has the old USGS streams but also the high resolution streams derived from the lidar data using the methodology developed for EDNA, so one can nicely demonstrate how the small scale (in cartographic sense) national data are inaccurate when one would try to use it a local scale (also how you would damage your DEM if you would have tried to use them for stream enforcement).