文献类型：期刊文献

英文题名：Synthesis of Leaf-on and Leaf-off Unmanned Aerial Vehicle (UAV) Stereo Imagery for the Inventory of Aboveground Biomass of Deciduous Forests

作者：Ni, Wenjian[1,2] Dong, Jiachen[1,2] Sun, Guoqing[3] Zhang, Zhiyu[1] Pang, Yong[4] Tian, Xin[4] Li, Zengyuan[4] Chen, Erxue[4]

第一作者：Ni, Wenjian

通信作者：Ni, WJ[1];Ni, WJ[2]

机构：[1]Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China;[2]Univ Chinese Acad Sci, Beijing 100049, Peoples R China;[3]Univ Maryland, Dept Geog Sci, College Pk, MD 20740 USA;[4]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China

年份：2019

卷号：11

期号：7

外文期刊名：REMOTE SENSING

收录：;EI(收录号：20193107252333);Scopus(收录号：2-s2.0-85069887468);WOS:【SCI-EXPANDED(收录号:WOS:000465549300154)】；

基金：This work was funded in part by the National Key R&D Program of China under Grant 2017YFA0603002, National Basic Research Program of China (Grant No. 2013CB733404, 2013CB733401), and in part by the National Natural Science Foundation of China (Grant Nos. 41471311, 41371357, 41301395).

语种：英文

外文关键词：forest aboveground biomass; stereo imagery; unmanned aerial vehicles; UAV; AGB; leaf-on; leaf-off; inventory

摘要：Applications of stereo imagery acquired by cameras onboard unmanned aerial vehicles (UAVs) as practical forest inventory tools are hindered by the unavailability of ground surface elevation. It is still a challenging issue to remove the elevation of ground surface in leaf-on stereo imagery to extract forest canopy height without the help of lidar data. This study proposed a method for the extraction of forest canopy height through the synthesis of UAV stereo imagery of leaf-on and leaf-off, and further demonstrated that the extracted forest canopy height could be used for the inventory of deciduous forest aboveground biomass (AGB). The points cloud of the leaf-on and leaf-off stereo imagery was firstly extracted by an algorithm of structure from motion (SFM) using the same ground control points (GCP). The digital surface model (DSM) was produced by rasterizing the point cloud of UAV leaf-on. The point cloud of UAV leaf-off was processed by iterative median filtering to remove vegetation points, and the digital terrain model (DTM) was generated by the rasterization of the filtered point cloud. The mean canopy height model (MCHM) was derived from the DSM subtracted by the DTM (i.e., DSM-DTM). Forest AGB maps were generated using models developed based on the MCHM and sampling plots of forest AGB and were evaluated by those of lidar. Results showed that forest AGB maps from UAV stereo imagery were highly correlated with those from lidar data with R-2 higher than 0.94 and RMSE lower than 10.0 Mg/ha (i.e., relative RMSE 18.8%). These results demonstrated that UAV stereo imagery could be used as a practical inventory tool for deciduous forest AGB.