基于LiDAR数据的城市道路提取与重建

本文借助于GIS强大的空间数据管理和分析功能,以Lidar点云数据为数据源,对交通信息系统基础空间数据进行快速采集和更新。文章并且在前人工作的基础上,提出了一种新的基于四维Hough变换的Lidar数据的提取和分类方法,对提取的道路信息进行重构。实践证明,此方法较之传统Lidar数据分类和提取方法,能够有效地解决其计算量过大、噪声过于敏感、道路边缘方向不平行等问题,实现道路的自动提取。

Extracting and reconstructing urban roads information based on Lidar data

With a strong GIS spatial data management and analysis functions,the paper used lidar point cloud data to quickly collect and update the space-based data of traffic information systems.In detail,on the basis of the predecessors' work,the paper put forward a new method of extracting and classifying lidar data based on four-dimensional Hough transform,then reconstructed the extracted roads information.It was practically proved that this method could be much effective to automatically classify and extract roads information of Lidar data than traditional methods with efficiently solving the problems including large calculation,extremely sensitive noises and nonparallel road edges.