A GRASS GIS Study of Open Data 1-meter NED DEM Resampling: Comparing recently published 1-meter NED to 3DEP LiDAR-derived original product resolution DEMs.

Session details
Status: 
Accepted
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Experience level: 
Beginner

The US Geological Survey (USGS) publishes 3D Elevation Program (3DEP) LiDAR data products as a free and open data resource through the National Map (TNM).  Digital Elevation Models (DEM) from this program include both 1-meter resolution seamless National Elevation Dataset (DEM) data as well as the native Original Product Resolution (OPR) data which comprise the source material for the NED DEM data.  This study uses open source software to explore potential differences between these two open datasets.  Recently published (2017) DEM data from seven (7) different project sites across four (4) different States west of the Mississippi River were analyzed in GRASS GIS.  DEM difference analysis using r.mapcalc in GRASS GIS revealed subtle vertical differences in the resampled 1-m NED when compared to its original source (OPR) dataset.  These DEM differences are accentuated by terrain and become more significant on slopes greater than ten (10) degrees.  Over such areas, the GRASS GIS computed standard deviation of the difference maps revealed vertical differences on the order of about ten (10) centimeters (cm).  Using the GRASS GIS command r.resamp.stats, an analog DEM to the 1-m NED can be created from the OPR DEM which effectively mitigates vertical discrepancies.  For OPR DEM data in a spatial reference system (SRS) other than UTM, GRASS GIS can also handle reprojection and scaling.  In the era of Big Data, GRASS offers a rapid and powerful workflow to assess and visualize open data that could even be programmed/scripted to handle very large area or even national-level analysis.  Analytical capabilities of Free and Open-Source Software (FOSS) tools allow users to make informed decisions in determining the best data product selection for a given requirement or application. 

Schedule info
Session Time Slot(s): 
Monday, May 14, 2018 - 16:30 to 17:05

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