一种基于点云数据的单木几何参数提取方法

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中图分类号：S771；TP391 文献标识码：A 文章编号：2095-5553（2025）08-0097-06

Abstract：Inresponse totheproblems oflarge erors and loweficiency inobtaining treesharpness and verticalityparameters usingtraditional manual measurement methods，this paper proposes a single tree verticalityand sharpness extraction method based on point cloud data.By slicing single treetrunks and projecting them onto atwo-dimensional plane，a densityclustering algorithm was used to identify the main point cloud clusters.RANSAC（Random Sample Consensus）was used to generate the best-fiting circleforthedistribution morphologyof the pointcloud clusters.Byfiting thediameterofthe best-fiting circle forthe main trunk at different heights，the sharpnessofthe tree was calculated basedon STM（Segmented Trimming Method）.Theextractionof theskeleton lineofasingle trunk wasachieved byconnecting thecenters ofadjacentslices and wasthen fitedtocalculate theverticality.Theexperimentalresultsshowthatthe methodachievedadetermination coefficient R2 of O.825 3 for sharpness calculation and O.8171 for verticalitycalculation.The method proposed in this article provides a new approach for extracting the two geometric parameters of tree sharpnessand verticality.

Keywords：single tree；laser point cloud；skeleton model；sharpness；verticality

0 引言

尖削度和垂直度是反映树木长势和笔直程度的几何参数，是林业调查中的重要指标。（剩余8594字）