srtm dem correction in vegetated mountain areas through the integration of spaceborne lidar, airborne lidar, and optical imagery

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ID: 243968
2015
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Ranked #89 of 499 articles by views in Journal of pharmacological sciences

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Résumé
The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is one of the most complete and frequently used global-scale DEM products in various applications. However, previous studies have shown that the SRTM DEM is systematically higher than the actual land surface in vegetated mountain areas. The objective of this study is to propose a procedure to calibrate the SRTM DEM over large vegetated mountain areas. Firstly, we developed methods to estimate canopy cover from aerial imagery and tree height from multi-source datasets (i.e., field observations, airborne light detection and ranging (LiDAR) data, Geoscience Laser Altimeter System (GLAS) data, Landsat TM imagery, climate surfaces, and topographic data). Then, the airborne LiDAR derived DEM, covering ~5% of the study area, was used to evaluate the accuracy of the SRTM DEM. Finally, a regression model of the SRTM DEM error depending on tree height, canopy cover, and terrain slope was developed to calibrate the SRTM DEM. Our results show that the proposed procedure can significantly improve the accuracy of the SRTM DEM over vegetated mountain areas. The mean difference between the SRTM DEM and the LiDAR DEM decreased from 12.15 m to −0.82 m, and the standard deviation dropped by 2 m.
Clé de Référence
su2015remotesrtm Utilisez cette clé pour citer automatiquement dans le manuscrit lors de l'utilisation de SciMatic Manuscript Manager ou Thesis Manager
Auteurs ;Yanjun Su;Qinghua Guo;Qin Ma;Wenkai Li
Revue Journal of pharmacological sciences
Année 2015
DOI
10.3390/rs70911202
URL
http://www.mdpi.com/2072-4292/7/9/11202
Mots-clés
lidar dem vegetation canopy height

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