Title :
3D reconstruction of a single tree from terrestrial LiDAR data
Author :
Wang Xiangyu ; Xie Donghui ; Yan Guangjian ; Zhang Wuming ; Wang Yan ; Chen Yiming
Author_Institution :
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
Abstract :
Terrestrial LiDAR systems have received lots of attention on three-dimensional (3D) structure reconstruction for trees, especially on the branches skeleton generation. On this basis, a method is proposed to add leaves structures based on point density by dividing small cube in the canopy to reduce the influence of uneven distribution of point cloud, combining gap fraction model to retrieve leaf area of a tree using terrestrial LiDAR data. It is successfully applied to reconstruct 3D trees using points data simulated by ray tracing algorithm as well as field measured points data. The relative error of leaf area between reconstructed and real structure is less than 0.9%. Meanwhile, the most relative error of directional gap fraction is also less than 4.1%. The experimental results prove that the method has gotten a satisfied consistency on visual sense and quantitative evaluation between the 3D structure reconstructed and real structure.
Keywords :
geophysical techniques; optical radar; vegetation; 3D structure reconstruction quantitative evaluation; branch skeleton generation; canopy small cube division; data simulated point; field measured point data; gap fraction model; leave structure; point density; ray tracing algorithm; real structure quantitative evaluation; relative directional gap fraction error; relative leaf area error; single tree 3D reconstruction; terrestrial LiDAR data; terrestrial LiDAR system; tree leaf area retrieval; tree three-dimensional structure reconstruction; uneven point cloud distribution influence; visual sense; Biological system modeling; Data models; Laser radar; Ray tracing; Remote sensing; Three-dimensional displays; Vegetation; 3D reconstruction; Leaf; LiDAR; Point cloud; Single tree;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946544