基于分层格网点密度法的车载LiDAR点云单株树信息提取及精度分析

Information Extraction and Accuracy Analysis of Individual Tree in Vehicle-mounted LiDAR Point Cloud Based on Hierarchical Grid Point Density Method

本文基于分层格网点密度法实现了车载激光雷达(Light Detection And Ranging,LiDAR)点云数据中单株树信息的提取,并通过改变格网阈值研究了算法中出现的参数(格网大小、格网高度)以及点云数据中的噪声地物对单株树信息提取精度的影响。研究结果表明,采用分层格网点密度法,能有效地在点云数据中提取单株树的点云信息。

In this paper,the extraction of single tree information from LiDAR point cloud data was realized based on hierarchical grid point density method.The influence of parameters(grid size,grid height)and noise features in point cloud data on the extraction accuracy of single tree information was studied by changing grid threshold.The results showed that the hierarchical grid dot density method could effectively extract the point cloud information of a single tree from the point cloud data.