基于空间临近的森林样地树木点云分割方法

doi:10.3969/j.issn.0255-8297.2025.06.009

应用科学学报 ›› 2025, Vol. 43 ›› Issue (6): 1003-1014.doi: 10.3969/j.issn.0255-8297.2025.06.009

• 信号与信息处理 • 上一篇

基于空间临近的森林样地树木点云分割方法

闫振国¹, 陈杨¹, 刘如飞², 王金博¹, 张佳琦²

1. 山东省地质测绘院, 山东济南 250003;
2. 山东科技大学测绘空间信息学院, 山东青岛 266590

收稿日期:2024-11-25 发布日期:2025-12-19
通信作者: 陈杨,高级工程师,研究方向为地理信息和数据处理。E-mail:21722903@qq.com E-mail:21722903@qq.com
基金资助:
国家自然科学基金（No. 42106180）；山东省地质测绘院科技创新培育项目（No. KY202303）

Point Cloud Segmentation Method for Trees in Forest Sample Plots Based on Spatial Proximity

YAN Zhenguo¹, CHEN Yang¹, LIU Rufei², WANG Jinbo¹, ZHANG Jiaqi²

1. Shandong GEO-Surveying & Mapping Institute, Jinan 250003, Shandong, China;
2. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, Shandong, China

Received:2024-11-25 Published:2025-12-19

摘要/Abstract

摘要： 针对现有基于地面端的树木点云分割方法因局部与全局特征信息融合不足导致分割精度下降的问题，提出了一种基于空间邻近关系的森林样地树木分割方法。首先，通过构建八叉树索引建立空间关系并分离地面点，在此基础上，建立多阶段的随机森林模型实现树木点云渐进式分割，即利用树干截面的二维形态特征及空间特性准确分割树干点云；其次，基于树干点云的分割结果，利用优化的形状函数集合（ensemble of shape functions,ESF）特征描述算子获取树干与对应树冠点云间的空间连通特征，并结合树冠点云的维度特性对树冠点云进行分割；最后，对单棵树木进行结构参数的提取，并与实地测量值进行对比以完成精度评价。本文利用两组移动激光扫描点云进行实验，结果表明两组数据中树木分割的召回率分别为90.57%和90.05%，精确率分别为93.20%和95.47%。

关键词: 森林, 多阶段随机森林, 二维形态特征, 空间关系, 优化的形状函数集合特征

Abstract: To address the problem of reduced segmentation accuracy in current ground-based tree point cloud segmentation methods caused by insufficient integration of local and global feature information, this paper proposes a tree segmentation method for forest sample plots based on spatial proximity relationship. This method first establishes the spatial relationship and separates the ground points by constructing an octree index. On this basis, a multi-stage random forest model is developed to achieve progressive segmentation of the tree point cloud. Specifically, the two-dimensional morphological features and spatial properties of tree trunk cross-section are used to accurately segment tree trunk point cloud. Subsequently, based on the segmentation results, the optimized ensemble of shape functions (ESF) feature description operator is used to obtain the spatial connectivity features between the tree trunk and the corresponding tree crown point cloud, enabling crown segmentation by incorporating dimensional properties of the tree crown point cloud. Finally, the structural parameters are extracted for single trees and validated against field measurements. Experiments using two sets of mobile laser scanning point cloud data show that the proposed method achieves tree segmentation recall rates of 90.57% and 90.05%, with accuracies of 93.20% and 95.47%, respectively.

Key words: forest, multi-stage random forest, two-dimensional morphological feature, spatial relationship, optimized ensemble of shape functions (ESF) feature

中图分类号:

TP391.7

闫振国, 陈杨, 刘如飞, 王金博, 张佳琦. 基于空间临近的森林样地树木点云分割方法[J]. 应用科学学报, 2025, 43(6): 1003-1014.

YAN Zhenguo, CHEN Yang, LIU Rufei, WANG Jinbo, ZHANG Jiaqi. Point Cloud Segmentation Method for Trees in Forest Sample Plots Based on Spatial Proximity[J]. Journal of Applied Sciences, 2025, 43(6): 1003-1014.

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基于空间临近的森林样地树木点云分割方法

Point Cloud Segmentation Method for Trees in Forest Sample Plots Based on Spatial Proximity

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