文献类型：会议论文

英文题名：Subtropical forest biomass estimation using airborne LiDAR and Hyperspectral data

作者：Pang, Yong[1] Li, Zengyuan[1] Meng, Shili[1] Jia, Wen[1] Liu, Luxia[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

会议论文集：23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)

会议日期：JUL 12-19, 2016

会议地点：Prague, CZECH REPUBLIC

语种：英文

外文关键词：Subtropical Forest; Biomass; Airborne Lidar; Hyperspectral; Fusion

年份：2016

摘要：Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF's (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.