倪文俭等:Characterization of ASTER GDEM elevation data over vegetated area compared with lidar data
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2015-04-03
Characterization of ASTER GDEM elevation data over vegetated area compared with lidar data
作者:Ni, WJ (Ni, Wenjian)[ 1,2 ] ; Sun, GQ (Sun, Guoqing)[ 2 ] ; Ranson, KJ (Ranson, Kenneth J.)[ 3 ]
INTERNATIONAL JOURNAL OF DIGITAL EARTH
卷: 8  期: 3  页: 198-211
DOI: 10.1080/17538947.2013.861025
出版年: MAR 4 2015
 
摘要
Current researches based on areal or spaceborne stereo images with very high resolutions (<1 m) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is the state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 m) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that the accurate coregistration between ASTER GDEM and national elevation dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-second and further improved to 0.6 if only homogenous vegetated areas were considered.
 
通讯作者地址: Ni, WJ (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
[ 2 ] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
显示增强组织信息的名称 [ 3 ] NASA, Goddard Space Flight Ctr, Biospher Sci Branch, Greenbelt, MD 20771 USA