Remote Sensing, Vol. 14, Pages 2000: Evaluating Vertical Accuracies of Open-Source Digital Elevation Models over Multiple Sites in China Using GPS Control Points (Remote Sensing)

Digital elevation models (DEMs) are widely used across a range of fields. Several open-source global DEMs have been released, including the advanced land observing satellite world 3D 30 m DEM (AW3D30DEM), advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTMDEM), and TerraSAR-X for digital elevation measurement (TanDEM-X). ASTER and SRTM are the most widely used DEMs, while the newer models AW3D30DEM and TanDEM-X are becoming increasingly popular. Many studies have evaluated the qualities of these DEMs; however, few multi-regional studies have been conducted in China. To comprehensively and systematically evaluate the qualities of these DEMs in China, the vertical accuracies of AW3D, ASTER, STRM (all 30 m), and TanDEM-X (90 m) were tested across 16 regions in China. Using high-precision global positioning system control points for reference, error values were determined by subtracting these reference values from corresponding global DEM elevation values. As the study only covered flat areas (slope < 5°), slope was treated as a controlled variable. After assessing the impacts of the slope aspect and land cover type, variations in vertical accuracy were examined with respect to longitude and latitude. Overall, TanDEM-X exhibited the highest stability and accuracy, AW3D30 and SRTM also performed well, while ASTER exhibited the worst accuracy. The DEMs showed relationships with the slope aspect and land cover type, assuming that slope had no influence on vertical accuracy. In general, vertical accuracy in high latitudes was slightly better than that in low latitudes, and no evident variations were observed with respect to longitude. This study is the first to conduct DEM analysis across many regions in China from open sources. Since most of the users rely on public domain DEM datasets, this work contributes to their analysis in academic and engineering fields.