Forest Canopy Height Extraction in Rugged Areas With ICESat/GLAS Data

被引：35
|
作者：
Wang, Xiaoyi [1 ,2 ]
Huang, Huabing [1 ,3 ]
Gong, Peng [1 ,3 ,4 ,5 ]
Liu, Caixia [1 ,2 ]
Li, Congcong [6 ]
Li, Wenyu [1 ,2 ]
机构：
[1] Chinese Acad Sci, Jointly Sponsored Inst Remote Sensing & Digital E, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Beijing Normal Univ, Beijing 100101, Peoples R China
[4] Tsinghua Univ, Ctr Earth Syst Sci, Key Lab Earth Syst Modeling, Minist Educ, Beijing 100084, Peoples R China
[5] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA
[6] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China
来源：
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2014年 / 52卷 / 08期
关键词：
Forest inventory; global forest monitoring; LASER ALTIMETER; VEGETATION; GLAS; DIFFERENTIATION; LVIS;
D O I：
10.1109/TGRS.2013.2283272
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
Geoscience Laser Altimeter System data have been widely used in forest canopy height extraction. It is still challenging over rugged areas. In this paper, we propose a forest canopy height extraction method consisting of the Savitzky-Golay filter and fitting, Sigbeg determination based on the fitting results, and slope correction for rugged areas, particularly for slopes ranging from 5 degrees to 15 degrees. The method was applied to both the Xinlin Forest, China, and Santa Rosa National Park, Costa Rica. The performance of this method was validated by field measurement and Laser Vegetation Imaging Sensor data. The goodness of fit (R-2) reached 0.73 and 0.78, respectively, and root-mean-squared errors (RMSEs) were 2.27 and 3.75 m over the two areas, respectively.
引用
收藏
页码：4650 / 4657
页数：8
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