Vertical Accuracy Assessment of ASTER and SRTM Digital Elevation Models: A case Study of Khartoum and Atbara / Port Sudan Railway, Sudan

Satellites like the Shuttle Radar Topography Mission (SRTM) and the Advanced Space-Based Thermal Emission and Reflection Radiometer (ASTER) continuously provide updated and high-resolution geospatial data. For instance, SRTM leverages satellite imagery to generate a high-resolution Digital Elevation Model (DEM) covering roughly 80% of Earth’s surface. DEMs depict Earth’s surface topography, supporting various geospatial fields like cartography and geology. This study assesses the vertical accuracy of SRTM and ASTER DEMs within Sudan. Local heights derived from GPS leveling data serve as reference points for comparison with both DEMs at one-arc-second precision. Field campaigns were conducted into two designated study areas to collect GPS-derived elevation data. Ground Control Points (GCPs) obtained from processed data were imported into ArcGIS 10.4 for point sampling. Elevation values for each GCP were then extracted from both ASTER and SRTM DEMs. To assess the accuracy of DEMs, statistical analysis through the standard deviation was performed in Microsoft Excel. This analysis quantified the residual errors between the reference GPS elevations and the corresponding DEM elevations for each study area. The precision of ASTER and SRTM measurements were 1.6508m and 10.1234m, respectively, for one research region. In another study area, the precision of ASTER and SRTM measurements were 1.8091m and 7.9521m, in succession. The results demonstrate that SRTM DEM exhibits superior statistical accuracy compared to ASTER DEM in both study areas. This suggests that SRTM data offers a more reliable foundation for various geospatial application in Sudan. This study underscores the significance of evaluating DEM accuracy for specific geographic regions. Moreover, the SRTM DEM provides a more statistically robust elevation dataset compared to ASTER DEM within the context of Sudan. These results can be valuable for researchers and practitioners who rely on DEMs for diverse geospatial analyses.