文献类型：会议论文

英文题名：ESTIMATING EFFECTIVE LEAF AREA INDEX USING LI-STRAHLER GEOMETRIC-OPTICAL MODEL, LANDSAT 7 ETM+, AND AIRBORNE LIDAR IN THE GREATER KHINGAN MOUNTAINS OF CHINA

作者：Gu, Chengyan[1] Wang, Chongyang[2] Tian, Xin[2] Li, Zengyuan[2] Sun, Shanshan[2] Gao, Zhihai[2]

第一作者：Gu, Chengyan

通信作者：Tian, X[1];Li, ZY[1]

机构：[1]Natl Forestry & Grassland Adm, Planning & Design Inst Forestry Prod Ind, 130 Chaoyangmennei St, Beijing 100010, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Dongxiaofu 1,Xiangshan Rd, Beijing 100091, Peoples R China

会议论文集：IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

会议日期：JUL 28-AUG 02, 2019

会议地点：Yokohama, JAPAN

语种：英文

外文关键词：Effective leaf area index; Li-Strahler geometric-optical model; Airborne LiDAR; Landsat 7 ETM+ data

年份：2019

摘要：Accurate estimation of forest effective leaf area index (LAIe) is of great significance for regional carbon sequestration studies, forest management and monitoring. In this study, an advanced method was developed to predict LAIe based on Li-Strahler geometric-optical model, airborne LiDAR and Landsat 7 ETM+ data. More specifically, based on the Li-Strahler geometric-optical model, a reliable method was developed to solve the mixed pixel problem, and further to realize the prediction of regional LAIe from airborne LiDAR and multispectral data. First, based on the airborne LiDAR-derived canopy height product, the LAIe was estimated over airborne LiDAR coverage. Second, the sunlit background component was calculated based on the simplified relationship with canopy gap, and LAIe. Then, the reflectance of sunlit background was calculated based on the linear decomposition model. Finally, the forest LAIe was estimated by using Li-Strahler geometric-optical model over the study area. Results showed that the retrieval method proposed in this study could be used effectively in the inversion of regional LAIe, with the significant coefficient of determination (R-2) was 0.81 and root mean square error (RMSE) was 0.23, as compared with field measurements.