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

doi:10.1016/j.isprsjprs.2015.10.007

CORC > 植物研究所 > 中国科学院植物研究所 > 植被与环境变化国家重点实验室

	Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories
	Tao, Shengli 3,4; Wu, Fangfang ; Guo, Qinghua 2; Wang, Yongcai ; Li, Wenkai 5; Xue, Baolin ; Hu, Xueyang 3,4; Li, Peng 3,4; Tian, Di 3,4; Li, Chao 3,4
刊名	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
	2015
卷号	110 页码:66-76
关键词	Terrestrial LiDAR Segmentation Shortest path Mobile LiDAR Metabolic ecology theory DBSCAN
ISSN号	0924-2716
DOI	10.1016/j.isprsjprs.2015.10.007
文献子类	Article
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.
学科主题	Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
电子版国际标准刊号	1872-8235
出版地	AMSTERDAM
WOS关键词	INDIVIDUAL TREES ; STEM VOLUME ; LASER ; HEIGHT ; FORM ; SEGMENTATION ; DENSITY ; CLASSIFICATION ; IDENTIFICATION ; ALLOMETRY
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000366225400007
资助机构	National Natural Science Foundation of China [41471363, 31321061, 31330012, 31270563, 41401505] ; National Science Foundation [DBI 1356077]
内容类型	期刊论文
源URL	[http://ir.ibcas.ac.cn/handle/2S10CLM1/25872]
专题	植被与环境变化国家重点实验室
作者单位	1.Sun Yat Sen Univ, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Guangdong, Peoples R China 2.Peking Univ, Minist Educ, Key Lab Earth Surface Proc, Beijing 100871, Peoples R China 3.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 4.Peking Univ, Coll Urban & Environm Sci, Dept Ecol, Beijing 100871, Peoples R China 5.Univ Calif Merced, Sch Engn, Sierra Nevada Res Inst, Merced, CA 95343 USA
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,2015,110:66-76.
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,110,66-76.
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 110(2015):66-76.