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自然资源遥感  2024, Vol. 36 Issue (3): 81-87    DOI: 10.6046/zrzyyg.2023112
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
地基激光雷达单木树冠体积提取球坐标积分法
麻卫峰1,2,3(), 吴小东2,4, 王冲2, 闻平2, 王金亮1,3, 曹磊2, 肖正龙2
1.云南师范大学地理学部,昆明 650500
2.中国电建集团昆明勘测设计研究院有限公司,昆明 650000
3.云南省地理空间信息工程技术研究中心,昆明 650500
4.云南大学国际河流与生态安全研究院,昆明 650500
A spherical coordinate integration method for extracting crown volumes of individual trees based on the TLS point clouds
MA Weifeng1,2,3(), WU Xiaodong2,4, WANG Chong2, WEN Ping2, WANG Jinliang1,3, CAO Lei2, XIAO Zhenglong2
1. Faculty of Geography, Yunnan Normal University, Kunming 650500, China
2. Power China Kunming Engineering Corporation Limited, Kunming 650000, China
3. Center for Geospatial Informatin Engineering and Technology of Yunnan Province, Kunming 650500, China
4. Institute of International Rivers and Eco-security, Yunnan University, Kunming 650500, China
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摘要 

树冠体积是地表生态监测研究的关键因子,激光点云可精细描述单木空间形态,为树冠体积提取提供了数据基础,但现有的激光点云单木树冠提取方法存在参数敏感、自动化程度不高等不足。文章在分析单木三维空间形态结构的基础上,提出了一种基于地基激光点云数据的单木树冠体积提取球坐标积分法。首先,根据激光点云高程分布特性,采用可视高程阈值分割得到树冠点; 然后,将激光点云投影至三维球坐标空间并进行四棱锥形微元分割; 最后,利用三维球坐标积分确定树冠体积。选择6种不同类型的单木激光点云数据进行试验,结果表明: 文章方法能较好地顾及树冠形态、点云密度等因素,单木树冠体积提取绝对误差绝对值最大值为2.33 m3,相对误差最大值为3.40%,相比已有方法具有树冠提取精度高、稳定性好的优势。该研究对激光点云林木参数提取具有重要的参考价值。

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麻卫峰
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闻平
王金亮
曹磊
肖正龙
关键词 树冠体积激光点云球坐标微元体    
Abstract

Crown volumes serve as a crucial factor for surface ecological monitoring. Laser point clouds can characterize the fine-scale spatial morphologies of individual trees, providing a data basis for crown volume extraction. However, existing laser point cloud-based methods for extracting crown volumes of individual trees are sensitive to parameters and exhibit low degrees of automation. Based on the analysis of the three-dimensional morphological structures of individual trees, this study proposed a spherical coordinate integration method for extracting crown volumes of individual trees based on the terrestrial laser scanning (TLS) point clouds. First, the crown points were obtained through visual elevation threshold-based segmentation according to the elevation distributions of TLS point clouds. Then, the TLS point clouds were projected onto the spherical coordinate space for infinitesimal segmentation into triangular pyramids. Finally, the crown volumes were determined through the three-dimensional spherical coordinate integration. Six types of TLS point cloud data for individual trees were selected for tests. As indicated by the test results, the proposed method effectively considers factors like crown morphology and point cloud density, achieving a maximum absolute error of 2.33 m3 and a maximum relative error of 3.40% in the crown volume extraction of individual trees. It manifests higher extraction accuracy and stability compared to the existing methods. Therefore, this study holds significant reference value for extracting tree parameters based on TLS point clouds.

Key wordscrown volume    TLS point cloud    spherical coordinate    infinitesimal element
收稿日期: 2023-04-26      出版日期: 2024-09-03
ZTFLH:  TP79  
基金资助:国家自然科学基金项目“联合ULS与TLS点云数据的滇西北天然林单木生物量估算研究”(41961060);云南省基础研究计划项目“机载LiDAR输电线路本体参数化建模方法研究”(202401AT070111)
作者简介: 麻卫峰(1987-),男,讲师,主要从事激光雷达技术与应用研究。Email: 2433278222@qq.com
引用本文:   
麻卫峰, 吴小东, 王冲, 闻平, 王金亮, 曹磊, 肖正龙. 地基激光雷达单木树冠体积提取球坐标积分法[J]. 自然资源遥感, 2024, 36(3): 81-87.
MA Weifeng, WU Xiaodong, WANG Chong, WEN Ping, WANG Jinliang, CAO Lei, XIAO Zhenglong. A spherical coordinate integration method for extracting crown volumes of individual trees based on the TLS point clouds. Remote Sensing for Natural Resources, 2024, 36(3): 81-87.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2023112      或      https://www.gtzyyg.com/CN/Y2024/V36/I3/81
Fig.1  地基激光点云树冠体积提取主要技术流程
Fig.2  可视化最佳高程阈值分割的树冠提取
Fig.3  树冠三维球坐标系定义
Fig.4  树冠点云微元体
Fig.5  单木激光点云实验数据
实验数据 高度/m 点云数 点间距/m 树冠形态描述
桂花点云 5.03 54 557 0.011 空间球体,轮廓规则,侧视“O”型
雪松点云 10.58 127 976 0.015 三棱锥,轮廓规则,侧视倒“V”型
香樟点云 6.73 46 926 0.023 空间椭球,轮廓规则,侧视“O”型
滇朴点云 14.46 287 145 0.012 圆柱体,轮廓极不规则,侧视“X”型
银杏点云 8.28 39 667 0.026 三棱锥,轮廓较规则,侧视倒“V”型
樱花点云 6.66 36 834 0.022 三棱锥,轮廓极不规则,侧视“V”型
Tab.1  实验数据基本信息统计
实验数据 参考值 点云边界检测法 点云分层法 本文方法
提取
结果/m3
提取
结果/m3
绝对
误差/m3
相对
误差/%
提取
结果/m3
绝对
误差/m3
相对
误差/%
提取
结果/m3
绝对
误差/m3
相对
误差/%
桂花点云 12.96 13.17 0.21 1.62 12.12 -0.84 6.48 13.19 0.23 1.77
雪松点云 36.49 35.73 -0.76 2.08 37.51 1.02 2.80 36.04 -0.45 1.23
香樟点云 13.26 13.87 0.61 4.60 12.29 -0.97 7.32 13.42 0.16 1.21
滇朴点云 68.51 65.32 -3.19 4.66 71.97 3.46 5.05 66.18 -2.33 3.40
银杏点云 22.27 20.37 -1.9 8.53 21.77 -0.5 2.25 22.63 0.36 1.62
樱花点云 7.48 7.12 -0.36 4.81 8.39 0.91 12.17 7.27 -0.21 2.81
Tab.2  激光点云树冠体积提取及精度分析
Fig.6  树冠提取结果精度指标分布曲线
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