利用倾斜摄影三维点云制作数字高程模型技术方法

Technical Method of Producing Digital Elevation Model Using Oblique Photography 3D Point Cloud

摘要: 对SOR滤波后的点云进行布料模拟滤波处理是大规模自动化生成数字高程模型(DEM)的关键技术，但是，如何从点云中“剔除”树木、房屋等点，只留下真正的地面点，从而生成DEM，技术方法仍然需要提升。本文基于Python开放生态，开发了一整套点云文件边界矢量提取、点云文件批量筛选、点云区块文件批量选择与复制、统计离群点移除滤波方法删除离群点、布料模拟滤波处理与参数确定的数据处理系统。利用该系统处理了甘肃某地区45平方公里的DEM，利用320个检查点对高程质量进行检查，高程点位中误差为0.087米，成果精度符合规范要求，为后续地理信息系统应用提供了可靠的基础数据。

Abstract: Fabric simulation filtering of SOR filtered point clouds is a key technology for large-scale automated generation of digital elevation models (DEMs), but how to “exclude” trees, houses and other points from point clouds, leaving only real ground points, so as to generate digital DEMs, the technical method still needs to be improved. Based on the Python open ecosystem, this paper develops a complete set of data processing systems for point cloud file boundary vector extraction, point cloud file batch filtering, point cloud block file batch selection and copying, statistical outlier removal filter method to delete outliers, cloth simulation filter processing and parameter determination. The system was used to process the DEM of 50 square kilometers in a certain area of Gansu, and the elevation quality was checked by 320 inspections. The error in the elevation point was 0.087 meters, and the accuracy of the results met the requirements of the specification, which provided reliable basic data for the subsequent application of geographic information system.