Difference between revisions of "Edu Data Package North Carolina"

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(Historical maps)
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* raw SRTM V2
 
* raw SRTM V2
 
* DRG topo sheets
 
* DRG topo sheets
 +
* Historical maps, e.g. [http://memory.loc.gov/cgi-bin/map_item.pl?data=/home/www/data/gmd/gmd388/g3881/g3881e/ct001099.jp2&style=gnrlmap&itemLink=r?ammem/gmd:@filreq(@field(NUMBER+@band(g3881e+ct001099))+@field(COLLID+gnrlmap))&title=Map%20of%20Virginia%20and%20West%20Va.,%20North%20%26%20part%20of%20South%20Carolina,%20Maryland%20%26%20Delaware,%20showing%20the%20situation%20in%20these%20states%20of%20schools%20taught%20by%20graduates%20of%20the%20Hampton%20Normal%20%26%20Agricultural%20Institute%20from%201871%20to%201876. Schools situation North Carolina 1871 to 1876]
 
* HydroSHEDS data (check if resolution is high enough)
 
* HydroSHEDS data (check if resolution is high enough)
  
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* streams from DEM
 
* streams from DEM
 
* derived satellite indices
 
* derived satellite indices
* hydrologically (kinematic wave) conditioned SRTM V2  
+
* hydrologically (kinematic wave) conditioned SRTM V2
  
 
=== VECTOR ===
 
=== VECTOR ===

Revision as of 04:44, 6 May 2006

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 (should be slightly more than Spearfish, around 20x20miles):

  • 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)


We should have a latlong location and a location in state plane coordinate system in meters - that is official for NC, but many organizations (counties, NC Flood) use feet...

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

The below list needs to be organized into thematic sets, such as baseline data, imagery, census, terrain, ... it is too messy now

RASTER

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 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)

Derived data (from vector maps, maybe not needed?):

  • DEM from Lidar vector points
  • streams from DEM
  • derived satellite indices
  • hydrologically (kinematic wave) conditioned SRTM V2

VECTOR

  • point data:
  • 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
    • ZIP codes

Packaging issues

  • convert feet to meters if needed
  • File Naming convention
  • Metadata management (most data include standard FGDC metadata)
  • 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).