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《Journal of Geo-Information Science》 2017-08
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Analysis and Comparison of SRTM1 DEM and ASTER GDEM V2 Data

WU Wenjiao;ZHANG Shifang;ZHAO Shangmin;College of Mining Engineering, Taiyuan University of Technology;  
Taking Shanxi Province as the research area, this paper compared the vertical accuracy of SRTM1 DEM and ASTER GDEM V2 data based on ICESat/GLA14 altimetry data. Firstly, error values for these two DEM datasets were acquired by taking ICESat/GLA14 data as the real data, and their error parameters were also calculated, such as mean error(ME), absolute mean error(AME), standard deviation(STD) and root mean square error(RMSE). Then, the error distribution of these two DEM datasets were analysed within the classes of slope, land use type and landform type. Finally, based on topographic profile method, the vertical error differences between these two DEM datasets in topographic types were analysed. The research results showed:(1) The vertical accuracy of SRTM1 DEM data is significantly higher than that of ASTER GDEM V2 data. The RMSE values of SRTM1 DEM and ASTER GDEM V2 are 6.1 m and 10.7 m, respectively.(2) Error analysis based on slope factor showed that the vertical accuracy of these two DEM datasets is affected seriously by the slope, and the error value increases with the increase of the slope value. Error analysis based on land use factor showed that the AME, STD and RMSE values of SRTM1 DEM are the lowest in paddy field, the highest in forestland, and the three error parameters of ASTER GDEM V2 are the lowest in building and the highest in forestland. Error analysis based on landform type factor showed that the AME, STD and RMSE values of SRTM1 DEM and ASTER GDEM V2 data are the lowest in the plain area, and the highest in large fluctuation mountain area.(3) On the selected topographic profiles in plain and terrace areas, the elevation value of ASTER GDEM V2 data have abnormal fluctuations. SRTM1 DEM data is too high for the estimation of valley. Overall,SRTM1 DEM is more accurate than ASTER GDEM V2 for terrain representation, which is basically consistent with ICESat/GLA14.
【Fund】: 国家自然科学基金项目(41301469、41171332);; 科技基础性工作专项项目(2011FY110400-2);; 测绘地理信息公益性行业科研专项项目(201512033)
【CateGory Index】: P208
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