IB-CAS  > 植被与环境变化国家重点实验室
A marker-free method for registering multi-scan terrestrial laser scanning data in forest environments
Guan, Hongcan1; Su, Yanjun1; Sun, Xiliang1; Xu, Guangcai1; Li, Wenkai2; Ma, Qin1; Wu, Xiaoyong1; Wu, Jin3; Liu, Lingli1; Guo, Qinghua1
2020
发表期刊ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN0924-2716
卷号166页码:82-94
摘要Terrestrial laser scanning (TLS) has been recognized as an accurate means for non-destructively deriving three-dimensional (3D) forest structural attributes. These attributes include but are not limited to tree height, diameter at breast height, and leaf area density. As such, TLS has become an increasingly important technique in forest inventory practices and forest ecosystem studies. Multiple TLS scans collected at different locations are often involved for a comprehensive characterization of 3D canopy structure of a forest stand. Among which, multi-scan registration is a critical prerequisite. Currently, multi-scan TLS registration in forests is mainly based on a very time-consuming and tedious process of setting up hand-crafted registration targets in the field and manually identifying the common targets between scans from the collected data. In this study, a novel marker-free method that automatically registers multi-scan TLS data is presented. The main principle underlying our method is to identify shaded areas from the raw point cloud of a single TLS scan and to use them as the key features to register multi-scan TLS data. The proposed method is tested with 17 pairs of TLS scans collected in six plots across China with various vegetation characteristics (e.g., vegetation type, height, and understory complexity). Our results showed that the proposed method successfully registered all 17 pairs of TLS scans with equivalent accuracy to the manual registration approach. Moreover, the proposed method eliminates the process of setting up registration targets in the field, manually identifying registration targets from TLS data, and processing raw TLS data to extract individual tree attributes, which brings it the advantages of high efficiency and robustness. It is anticipated that the proposed algorithms can save time and cost of collecting TLS data in forests, and therefore improves the efficiency of TLS forestry applications.
关键词Terrestrial laser scanning Registration Marker-free Forest
学科领域Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
DOI10.1016/j.isprsjprs.2020.06.002
收录类别SCI
语种英语
WOS关键词LEAF-AREA INDEX ; FREE REGISTRATION ; INDIVIDUAL TREES ; CLUMPING INDEX ; LIDAR DATA ; HEIGHT ; STEM ; CANOPY ; CLASSIFICATION ; ACCURACY
WOS研究方向Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000551268300008
出版者ELSEVIER
文献子类Article
出版地AMSTERDAM
EISSN1872-8235
资助机构Frontier Science Key Programs of the Chinese Academy of Sciences [QYZDY-SSW-SMC011] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41871332,31971575, 41901358]
作者邮箱guanhc@ibcas.ac.cn ; ysu@ibcas.ac.cn ; qguo@ibcas.ac.cn
引用统计
被引频次:18[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ibcas.ac.cn/handle/2S10CLM1/21666
专题植被与环境变化国家重点实验室
作者单位1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China
4.Univ Hong Kong, Sch Biol Sci, Pokfulam, Hong Kong, Peoples R China
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GB/T 7714
Guan, Hongcan,Su, Yanjun,Sun, Xiliang,et al. A marker-free method for registering multi-scan terrestrial laser scanning data in forest environments[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2020,166:82-94.
APA Guan, Hongcan.,Su, Yanjun.,Sun, Xiliang.,Xu, Guangcai.,Li, Wenkai.,...&Guo, Qinghua.(2020).A marker-free method for registering multi-scan terrestrial laser scanning data in forest environments.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,166,82-94.
MLA Guan, Hongcan,et al."A marker-free method for registering multi-scan terrestrial laser scanning data in forest environments".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 166(2020):82-94.
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