Hydrologic application comparison among typical open global DEM data based on remote sensing images

As the data source in digital topographic analysis, digital elevation model (DEM) data plays an important role in many fields, and hydrologic application is an important one among them. The successive release of open global DEM datasets provides multi choices for these applications, but also brings puzzles in DEM data selection. Taking Fenhe River Basin of China as the study area, this research compared the hydrologic networks extracted by typical global DEM data using matching difference (MD), correctness (C) and figure of merit (FM) indexes. Firstly, four DEM-derived hydrologic networks (DHNs) were acquired through topographic analysis using four typical global DEM datasets, including Shuttle Radar Terrain Mission (SRTM) data with 1 arc second resolution (SRTM1), SRTM data with 3 arc second resolution (SRTM3), ASTER global DEM data in the second version (GDEM-v2) and ALOS world 3D-30m (AW3D30) data. Then, the reference hydrologic network (RHN) was interpreted based on remote sensing images. Finally, the DHNs were evaluated and compared by referencing the RHN using different indexes. Research results show: (1) four DHNs have similar distribution in mountain regions but much different performance in flat regions; (2) all the indexes (including MD, C and FM) indicate that about the quality of the DHNs, the best is the AW3D30 data, then the SRTM1 data, the next is the SRTM3 data, and the GDEM-v2 data has the worst quality; (3) through analyzing the MD distribution in different slope classes for the four global DEM datasets, the MD mainly distributes in flat region, and then sloping region, but seldom in steep region. Overall, AW3D30 has the best quality, a little better than SRTM1 and much better than SRTM3 and GDEM-v2; SRTM3 and GDEM-v2 data have much worse quality, and GDEM-v2 data is the worst in the four global DEM datasets. Considering that the AW3D30 data is originated from the DEM dataset with 5m resolution, it may exerts more effect in future digital topographic analysis.