VERIFICATION OF LEAF AREA INDEX RETRIEVED BY ICESAT-2 PHOTON-COUNTING LIDAR WITH AIRBORNE LIDAR

被引：3
|
作者：
Wang, Yantian [1 ,2 ]
Wang, Cheng [1 ,2 ]
Yang, Xuebo [1 ]
Nie, Sheng [1 ]
机构：
[1] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源：
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
基金：
中国国家自然科学基金;
关键词：
Photon-counting LiDAR; airborne; LiDAR; leaf area index (LAI); verification;
D O I：
10.1109/IGARSS46834.2022.9884043
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Leaf area index (LAI) is a significant parameter controlling a lot of physical and biological processes related to vegetation on the Earth's surface. Previously, an LAI estimation model of ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2)/ATLAS (Advanced Topographic Laser Altimeter System) has been established and the accuracy of ICESat-2 LAI has been evaluated using optical images. However, this model hasn't been tested with airborne data. To demonstrate the effectiveness of ICESat-2 LAI, this study applied the model to airborne LiDAR data in the Saihanba National Nature Reserve in the same season. Results showed that the coefficient of determination (R-2) of ICESat-2 LAI was 0.63 and the root mean square error (RMSE) is 1.03(n = 26, p < 0.001), ICESat-2 has the inversion capability of LAI comparable to airborne lidar. These findings may help in promoting the LAI estimation model and broadening the application fields of the photon-counting LiDAR data.
引用
收藏
页码：7305 / 7308
页数：4
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