23 December 2017 Comparison of digital elevation models and relevant derived attributes
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The digital elevation model (DEM) and its derivative attributes are important parameters for evaluating any process using digital terrain analysis. Five freely available global DEM products including Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model version 2 (ASTER GDEM2), Shuttle Radar Topographic Mission version 4.1 (SRTM V4.1), Global Multiresolution Terrain Elevation Data 2010 (GMTED2010), EarthEnv-DEM90, and Global 30 Arc-Second Elevation (GTOPO30) were assessed in this study. The objective of this study was to compare the differences of elevations, slopes, and topographic wetness indices (TWIs) derived from these five DEM products. SRTM V4.1 showed a better accuracy [root mean square error (RMSE)=4.87  m] than ASTER GDEM2 (RMSE=7.08  m) based on ICESat/GLAS (the Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) laser altimetry points. ICESat/GLAS data were then selected as the benchmark to rectify the SRTM V4.1 data using the simple kriging (SK) interpolation method. The corrected high-accuracy SRTM V4.1 data (RMSE=1.14  m) were then regarded as the reference data. EarthEnv-DEM90 displayed the best accuracy in the DEM and slope, whereas the TWI accuracy of GMTED2010 was best. The accuracy of topographic attributes was sensitive to the roughness of the terrain. DEM and slope displayed a larger error variance as the elevation increased. DEM was sensitive to the data source and slope was sensitive to the data source and spatial resolution. TWI was influenced by data source and spatial resolution. As the spatial resolution decreased, the differences of topographic attributes tended to decrease.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Xinchuan Li, Xinchuan Li, Youjing Zhang, Youjing Zhang, Xiuliang Jin, Xiuliang Jin, Qiaoning He, Qiaoning He, Xiuping Zhang, Xiuping Zhang, } "Comparison of digital elevation models and relevant derived attributes," Journal of Applied Remote Sensing 11(4), 046027 (23 December 2017). https://doi.org/10.1117/1.JRS.11.046027 . Submission: Received: 13 July 2017; Accepted: 28 November 2017
Received: 13 July 2017; Accepted: 28 November 2017; Published: 23 December 2017

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