文献类型：期刊文献

英文题名：Estimation of forest canopy leaf area index using MODIS, MISR, and LiDAR observations

作者：Fu, Zhuo[1,2] Wang, Jindi[1] Song, Jin L.[1] Zhou, Hong M.[1] Pang, Yong[3] Chen, Bai S.[1,4]

第一作者：Fu, Zhuo

通信作者：Fu, Z[1]

机构：[1]Beijing Normal Univ, State Key Lab Remote Sensing Sci, Sch Geog, Beijing 100875, Peoples R China;[2]Satellite Environm Ctr, Minist Environm Protect, Beijing 100094, Peoples R China;[3]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing, Peoples R China;[4]Natl Engn Res Ctr Informat Technol Agr, Beijing, Peoples R China

年份：2011

卷号：5

期号：1

外文期刊名：JOURNAL OF APPLIED REMOTE SENSING

收录：;EI(收录号：20114214440237);Scopus(收录号：2-s2.0-80054078291);WOS:【SCI-EXPANDED(收录号:WOS:000291640300001)】；

基金：This research was supported in part by the Special Funds for Major State Basic Research Project (No. 2007CB714407 and No. 2007CB714404) and the National Natural Science Foundation of China (Grants No. 40871163 and No. 40701116), and the Open Funds of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing of China (No. 08zhong2).

语种：英文

外文关键词：GOMS model inversion; LAI; MODIS; MISR; LiDAR; forest

摘要：A new approach for determining the forest leaf area index (LAI) from a geometric-optical model inversion using multisensor observations is developed. For improving the LAI estimate for the forested area on rugged terrain, a priori information on tree height and the spectra of four scene components of a geometric-optical mutual shadowing (GOMS) model are extracted from airborne light-detection and ranging (LiDAR) data and optical remote sensing data with high spatial resolution, respectively. The slope and aspect of the study area are derived from digital elevation model data. These extracted parameters are applied in an inversion to improve the estimates of forest canopy structural parameters in a GOMS model. For the field investigation, a bidirectional reflectance factor data set of needle forest pixels is collected by combining moderate-resolution-imaging-spectroradiometer (MODIS) and multiangle-imaging-spectroradiometer (MISR) multiangular remote sensing observations. Then, forest canopy parameters are inverted based on the GOMS model. Finally, the LAI of the forest canopy of each pixel is estimated from the retrieved structural parameters and validated by field measurements. The results indicate that the accuracy of forest canopy LAI estimates can be improved by combining observations of passive multiangle and active remote sensors. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3594171]