Automatic dendrometry: Tree detection, tree height and diameter estimation using terrestrial laser scanning

被引:107
|
作者
Cabo, Carlos [1 ]
Ordonez, Celestino [1 ]
Lopez-Sanchez, Carlos A. [2 ]
Armesto, Julia [3 ]
机构
[1] Univ Oviedo, Dept Explotac & Prospecc Minas, Grp Invest Geomat & Computac Graf GEOGRAPH, Escuela Politecnia Mieres, Mieres 33600, Spain
[2] Univ Oviedo, Dept Biol Organismos & Sistemas, Grp Invest Sistemas Forestales Atlanticos GIS For, Escuela Politecnia Mieres, C Gonzalo Gutierres de Quiros S-N, Mieres 33600, Spain
[3] Univ Vigo, Dept Ingn Recursos Nat & Medio Ambiente, ETS Ingn Minas, Rua Maxwell,Campus Univ Lagoas Marcosende, Vigo 36310, Spain
关键词
TLS; Point clouds; DBH; Tree detection; Dendrometry; MEASURING FOREST STRUCTURE; STANDING TREES; LIDAR; INVENTORY; VOLUME; STEM; ACCURACY; SCANS;
D O I
10.1016/j.jag.2018.01.011
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
This study presents an automatic method to identify tree stems, and estimate tree heights and diameters from terrestrial laser scanning (TLS) data. The method is based on the isolation and vertical continuity of the stems. First, a height-normalized version of the point cloud is created. From this, stems are individualized, an iterative process is applied to the points at breast height for estimating diameters, and tree heights are calculated after denoising and clustering the points of each tree. The method was tested in three different sites. All the elements detected as trees were actual trees, and more than 99% of the trees in the plots were detected. Root mean square error (RMSE) of the estimated diameters at breast height (DBH) ranged from 0.8 to 1.3 cm in the test plots, and total tree height (TH) RMSE ranged from 0.3 to 0.7 m. In the cases studied, the algorithm showed robustness to the presence of steep or irregular terrain, the presence of low vegetation and artifacts at breast height, the indistinct use of individual or multiple scans, and tree density in the plot.
引用
收藏
页码:164 / 174
页数:11
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