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Point-cloud segmentation of individual trees in complex natural forest scenes based on a trunk-growth method

Journal of Forestry Research 2021年第6期32卷 2403-2414页

作者： Qianwei Liu Weifeng Ma Jianpeng Zhang Yicheng Liu Dongfan Xu Jinliang Wang Faculty of Geography Yunnan Normal UniversityKunming 650092YunnanPeople’s Republic of China Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan Kunming 650500YunnanPeople’s Republic of China Center for Geospatial Information Engineering and Technology of Yunnan Province Kunming 650500YunnanPeople’s Republic of China Forestry College Southwest Forestry UniversityKunming 650224YunnanPeople’s Republic of China

Forest resource management and ecological assessment have been recently supported by emerging *** laser scanning(TLS)is one that can be quickly and accurately used to obtain three-dimensional forest information,and create good representations of forest vertical *** data can be exploited for highly significant tasks,particularly the segmentation and information extraction for individual ***,the existing single-tree segmentation methods suffer from low segmentation accuracy and poor robustness,and hence do not lead to satisfactory results for natural forests in complex *** this paper,we propose a trunk-growth(TG)method for single-tree point-cloud segmentation,and apply this method to the natural forest scenes of Shangri-La City in Northwest Yunnan,***,the point normal vector and its Z-axis component are used as trunk-growth ***,the points surrounding the trunk are searched to account for ***,the nearest distributed branch and leaf points are used to complete the individual tree *** results show that the TG method can effectively segment individual trees with an average F-score of *** proposed method applies to many types of trees with various growth shapes,and can effectively identify shrubs and herbs in complex scenes of natural *** promising outcomes of the TG method demonstrate the key advantages of combining plant morphology theory and LiDAR technology for advancing and optimizing forestry systems.

关键词： Terrestrial laser scanning Point-cloud Northwest Yunnan Natural forests Single-tree segmentation trunk-growth

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