Segmenting tree crowns from terrestrial and mobile LiDAR data by   exploring ecological theories

doi:10.1016/j.isprsjprs.2015.10.007

CORC > 北京大学 > 城市与环境学院

	Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories
	Tao, Shengli ; Wu, Fangfang ; Guo, Qinghua ; Wang, Yongcai ; Li, Wenkai ; Xue, Baolin ; Hu, Xueyang ; Li, Peng ; Tian, Di ; Li, Chao ; Yao, Hui ; Li, Yumei ; Xu, Guangcai ; Fang, Jingyun
刊名	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
	2015
关键词	Terrestrial LiDAR Segmentation Shortest path Mobile LiDAR Metabolic ecology theory DBSCAN LASER-SCANNING DATA WAVE-FORM LIDAR INDIVIDUAL TREES STEM VOLUME FOREST BIOMASS HEIGHT SEGMENTATION DENSITY SIZE CLASSIFICATION
DOI	10.1016/j.isprsjprs.2015.10.007
英文摘要	The rapid development of light detection and ranging (LiDAR) techniques is advancing ecological and forest research. During the last decade, numerous single tree segmentation techniques have been developed using airborne LiDAR data. However, accurate crown segmentation using terrestrial or mobile LiDAR data, which is an essential prerequisite for extracting branch level forest characteristics, is still challenging mainly because of the difficulties posed by tree crown intersection and irregular crown shape. In the current work, we developed a comparative shortest-path algorithm (CSP) for segmenting tree crowns scanned using terrestrial (T)-LiDAR and mobile LiDAR. The algorithm consists of two steps, namely trunk detection and subsequent crown segmentation, with the latter inspired by the well-proved metabolic ecology theory and the ecological fact that vascular plants tend to minimize the transferring distance to the root. We tested the algorithm on mobile-LiDAR-scanned roadside trees and T-LiDAR-scanned broadleaved and coniferous forests in China. Point-level quantitative assessments of the segmentation results showed that for mobile-LiDAR-scanned roadside trees, all the points were classified to their corresponding trees correctly, and for T-LiDAR-scanned broadleaved and coniferous forests, kappa coefficients ranging from 0.83 to 0.93 were obtained. We believe that our algorithm will make a contribution to solving the problem of crown segmentation in T-LiDAR scanned-forests, and might be of interest to researchers in LiDAR data processing and to forest ecologists. In addition, our research highlights the advantages of using ecological theories as guidelines for processing LiDAR data. (C) 2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.; National Natural Science Foundation of China [41471363, 31321061, 31330012, 31270563, 41401505]; National Science Foundation [DBI 1356077]; SCI(E); EI; ARTICLE; guo.qinghua@gmail.com; 66-76; 110
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/424431]
专题	城市与环境学院
推荐引用方式 GB/T 7714	Tao, Shengli,Wu, Fangfang,Guo, Qinghua,et al. Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2015.
APA	Tao, Shengli.,Wu, Fangfang.,Guo, Qinghua.,Wang, Yongcai.,Li, Wenkai.,...&Fang, Jingyun.(2015).Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING.
MLA	Tao, Shengli,et al."Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2015).