A global corrected SRTM DEM product for vegetated areas. Issue 4 (3rd April 2018)

• Record Type: Journal Article
• Authors: Zhao, Xiaoqian; Su, Yanjun; Hu, Tianyu; Chen, Linhai; Gao, Shang; Wang, Rui; Jin, Shichao; Guo, Qinghua
• Is Part Of: Remote sensing letters. Volume 9:Issue 4(2018)
• Page Start: 393
• Page End: 402
• Publication Date: 2018-04-03
• Subjects: Remote sensing -- Periodicals; Remote sensing; Periodicals; 621.3678
• DOI: 10.1080/2150704X.2018.1425560
• Languages: English
• ISSNs: 2150-704X

Abstract

ABSTRACT: It has been found that the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is systematically higher than the actual land surface in vegetated areas. This study developed a new globally corrected SRTM DEM through reducing its systematic bias in vegetated areas. Over 150, 000 km 2 airborne light detection and ranging (LiDAR) data along with spaceborne LiDAR, global canopy height data, global canopy cover data and global land cover data were collected to correct the SRTM DEM. A linear regression based method was used to estimate the original SRTM DEM error and therefore correct the SRTM DEM data. The results show that the original SRTM DEM data is around 6 m higher than the actual land surfaces on average across all vegetation types. Our corrected SRTM DEM data can significantly reduce the significant bias to near zero, and can also reduce the root-mean-square error by 1 m.