RELATIVE ERROR EVALUATION TO TYPICAL OPEN GLOBAL DEM DATASETS IN SHANXI PLATEAU OF CHINA
Produced by radar data or stereo remote sensing image pairs, global DEM datasets are one of the most important types for DEM data. Relative error relates to surface quality created by DEM data, so it relates to geomorphology and hydrologic applications using DEM data. Taking Shanxi Plateau of China as the study area, this research evaluated the relative error to typical open 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 (AW3D) data. Through process and selection, more than 300,000 ICESat/GLA14 points were used as the GCP data, and the vertical error was computed and compared among four typical global DEM datasets. Then, more than 2,600,000 ICESat/GLA14 point pairs were acquired using the distance threshold between 100 m and 500 m. Meanwhile, the horizontal distance between every point pair was computed, so the relative error was achieved using slope values based on vertical error difference and the horizontal distance of the point pairs. Finally, false slope ratio (FSR) index was computed through analyzing the difference between DEM and ICESat/GLA14 values for every point pair. Both relative error and FSR index were categorically compared for the four DEM datasets under different slope classes. Research results show: Overall, AW3D has the lowest relative error values in mean error, mean absolute error, root mean square error and standard deviation error; then the SRTM1 data, its values are a little higher than AW3D data; the SRTM3 and GDEM-v2 data have the highest relative error values, and the values for the two datasets are similar. Considering different slope conditions, all the four DEM data have better performance in flat areas but worse performance in sloping regions; AW3D has the best performance in all the slope classes, a litter better than SRTM1; with slope increasing, the relative error for the SRTM3 data increases faster than other DEM datasets; so SRTM3 is better than GDEM-v2 in flat regions but worse in sloping regions. As to FSR value, AW3D has the lowest value, 4.37 %; then SRTM1 data, 5.80 %, similar to AW3D data; SRTM3 has higher value, about 8.27 %; GDEM-v2 data has the highest FSR value, about 12.15 %. FSR can represent the performance of correctly creating the earth surface based on DEM data. Hence, AW3D has the best performance, which is approximate to but a little better than SRTM1. The performance of SRTM3 and GDEM-v2 is similar, which is much worse than AW3D and SRTM1, and the performance of GDEM-v2 is the worst of all. Originated from the DEM dataset with 5m resolution, AW3D is regarded as the most precise global DEM datasets up to now, so it may exerts more effect in topographic analysis and geographic research. Through analysis and comparison of the relative error for the four open global DEM datasets, this research will provide reference in open global DEM datasets selection and applications in geosciences and other relevant fields.