一种基于机载LiDAR数据的山区道路提取方法  

A mountain road extraction method based on airborne LiDAR data

作　　者：刘国栋[1] 刘佳[1] 刘浪[1] LIU Guodong;LIU Jia;LIU Lang(School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China)

机构地区：[1]重庆交通大学土木工程学院,重庆400074

出　　处：《激光技术》2022年第4期466-473,共8页Laser Technology

基　　金：重庆市研究生教育优质课程建设计划资助项目(JDYZ2019009);重庆交通大学研究生课程思政示范项目(KCSZ2021010)。

摘　　要：为了解决基于机载激光雷达(LiDAR)点云提取道路时多重特征阈值设定难、普适性低的问题,采用了随机森林分类模型提取道路点云进而获得道路中心线的方法。首先使用渐进加密三角网滤波获取地面点云,根据山区道路特性,计算地面点云各点在邻域范围的坡度、粗糙度、高差方差、点密度及反射强度,组成点的分类特征;随后手动采集正负样本训练点云随机森林分类模型,将地面点云通过模型分类得到初始道路点云;再通过基于密度的噪声应用空间聚类算法去除噪声点精化道路点云;最后矢量化道路点云获取道路中心线。结果表明,以Entiat River地区山区LiDAR点云数据进行实验验证,道路点云提取的正确率达到95.29%,完整率达到92.96%,提取质量达到88.88%。该方法能解决多重阈值难以确定的问题,能较高精度地提取到山区道路点云,进而获取有效道路中心线,对山区道路信息的研究有一定的参考价值。In order to solve the problems of difficulty in setting multiple feature thresholds and low generality in road extraction based on airborne light detection and ranging(LiDAR)point cloud,a random forest classification model was used to extract road point cloud and then obtain road center line.Firstly,the ground point cloud was obtained by progressive cryptography triangulation filtering.According to the characteristics of mountain roads,the slope,roughness,height difference variance,point density and reflection intensity of each point in the neighborhood of the ground point cloud were calculated,and the classification characteristics of the component points were calculated.Then,positive and negative samples were collected manually to train the random forest classification model of point cloud.The ground point cloud was classified by the model to get the initial road point cloud.And then,the road point cloud was rifined through the algorithm of density-based spatial clustering of application with noise(DBSCAN).Finally,the road point cloud was vectored to obtain the road center line.The results show that the accuracy of road point cloud extraction is 95.29%,the integrity rate is 92.96%,and the extraction quality is 88.88%,respectively.This method can solve the problem of difficult to determine multiple thresholds,and can extract the mountain road point cloud with high precision,and then obtain the effective road center line,which has certain reference value for the study of mountain road information.

关 键 词：激光技术 山区道路 随机森林 激光雷达点云 基于密度的噪声应用空间聚类算法 

分 类 号：TN958.98[电子电信—信号与信息处理] P237[电子电信—信息与通信工程]