VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 2 OVER THE CONTERMINOUS UNITED STATES
- 1U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, South Dakota, USA 57198
- 2SGT, Inc., contractor to the USGS Earth Resources Observation and Science Center, Sioux Falls, South Dakota, USA 57198
- 3ERT, Inc., contractor to the USGS Earth Resources Observation and Science Center, Sioux Falls, South Dakota, USA 57198
Keywords: Accuracy, DEM/DTM, Comparison, Geodesy, Global-Environmental-Databases, Land Cover, Mapping, Satellite
Abstract. The ASTER Global Digital Elevation Model Version 2 (GDEM v2) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of –0.20 meters is a significant improvement over the GDEM v1 mean error of –3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures) cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height), GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.