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A marker-free method for registering multi-scan terrestrial laser scanning data in forest environments

文献类型：期刊论文

作者Guan, Hongcan4; Su, Yanjun4; Sun, Xiliang4; Xu, Guangcai4; Li, Wenkai3; Ma, Qin4; Wu, Xiaoyong4; Wu, Jin2; Liu, Lingli4; Guo, Qinghua4
刊名ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
出版日期2020
卷号166页码:82-94
关键词Terrestrial laser scanning Registration Marker-free Forest
ISSN号0924-2716
DOI10.1016/j.isprsjprs.2020.06.002
文献子类Article
英文摘要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.
学科主题Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
出版地AMSTERDAM
电子版国际标准刊号1872-8235
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
语种英语
WOS记录号WOS:000551268300008
出版者ELSEVIER
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]
源URL[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.Univ Hong Kong, Sch Biol Sci, Pokfulam, Hong Kong, Peoples R China
2.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
推荐引用方式
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.

入库方式： OAI收割

来源：植物研究所

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