文献类型： 外文期刊

作者： Lin, Jiayuan ² ; Wang, Meimei ³ ; Ma, Mingguo ¹ ; Lin, Yi ⁴ ;

作者机构： 1.Southwest Univ, Sch Geog Sci, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Chongqing 400715, Peoples R China

2.Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China

3.Sichuan Acad Agr Sci, Inst Remote Sensing Applicat, Chengdu 610066, Peoples R China

4.Peking Univ, Inst Remote Sensing & GIS, Beijing 100871, Peoples R China

关键词： Aboveground Biomass (AGB); subalpine coniferous forest; Unmanned Aerial Vehicles (UAV); oblique photograph; Aerial Triangulation (AT); point cloud; Canopy Height Model (CHM); allometric equation

期刊名称：REMOTE SENSING （ 影响因子：4.848； 五年影响因子：5.353 ）

ISSN： 2072-4292

年卷期： 2018 年 10 卷 11 期

页码：

收录情况： SCI

摘要： In tree Aboveground Biomass (AGB) estimation, the traditional harvest method is accurate but unsuitable for a large-scale forest. The airborne Light Detection And Ranging (LiDAR) is superior in obtaining the point cloud data of a dense forest and extracting tree heights for AGB estimation. However, the LiDAR has limitations such as high cost, low efficiency, and complicated operations. Alternatively, the overlapping oblique photographs taken by an Unmanned Aerial Vehicle (UAV)-loaded digital camera can also generate point cloud data using the Aerial Triangulation (AT) method. However, limited by the relatively poor penetrating capacity of natural light, the photographs captured by the digital camera on a UAV are more suitable for obtaining the point cloud data of a relatively sparse forest. In this paper, an electric fixed-wing UAV loaded with a digital camera was employed to take oblique photographs of a sparse subalpine coniferous forest in the source region of the Minjiang River. Based on point cloud data obtained from the overlapping photographs, a Digital Terrain Model (DTM) was generated by filtering non-ground points along with the acquisition of a Digital Surface Model (DSM) of Minjiang fir trees by eliminating subalpine shrubs and meadows. Individual tree heights were extracted by overlaying individual tree outlines on Canopy Height Model (CHM) data computed by subtracting the Digital Elevation Model (DEM) from the rasterized DSM. The allometric equation with tree height (H) as the predictor variable was established by fitting measured tree heights with tree AGBs, which were estimated using the allometric equation on H and Diameter at Breast Height (DBH) in sample tree plots. Finally, the AGBs of all of the trees in the test site were determined by inputting extracted individual tree heights into the established allometric equation. In accuracy assessment, the coefficient of determination (R-2) and Root Mean Square Error (RMSE) of extracted individual tree heights were 0.92 and 1.77 m, and the R-2 and RMSE of the estimated AGBs of individual trees were 0.96 and 54.90 kg. The results demonstrated the feasibility and effectiveness of applying UAV-acquired oblique optical photographs to the tree AGB estimation of sparse subalpine coniferous forests.