文献类型：会议论文

英文题名：CHINA TYPICAL FOREST ABOVEGROUND BIOMASS ESTIMATION BY FUSION OF MULTI-PLATFORM DATA

作者：Pang Yong[1] Li Zengyuan[1] Meng Shili[1,2] Lu Hao[1] Jia Wen[1] Liu Qingwang[1] Li Haikui[1] Lei Yuancai[1]

第一作者：庞勇

通信作者：Pang, Y[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing, Peoples R China;[2]Beijing Normal Univ, Coll Informat Sci & Technol, Beijing, Peoples R China

会议论文集：36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

会议日期：JUL 10-15, 2016

会议地点：Beijing, PEOPLES R CHINA

语种：英文

外文关键词：China forest; aboveground biomass; LiDAR; Field-Airborne-Spaceborne (FAS) observation; multi-platform

年份：2016

摘要：China has a wide variety of forest types. It is challenging to make a reliable estimation of these forest aboveground biomass (AGB) using geo-spatial technologies. We developed a Field-Airborne-Spaceborne (FAS) comprehensive observation method for AGB estimation. According to forest ecological zones of China, we carried out three FAS campaigns in the Northeast, central, and Southwest of China. Airborne LiDAR data were collected along National Forest Inventory (NFI) plots. Then the airborne LiDAR data were used to estimate AGB after been trained by NFI plots. Then these LiDAR estimated AGB were used to train satellite data for large area biomass mapping. The stratified regression tree modeling method was used in this research. The overall estimation correlation coefficient are better than 0.8.