复杂城区车载激光扫描点云分层路段定位与数据纠正实验研究

高精度的车载点云数据是实现各种城市地物要素提取的前提,但在复杂城市环境下车载作业时信号遮挡、衰减和多径效应频繁发生,进而造成点云数据精度严重降低,如何对复杂环境下的点云数据进行分析和纠正就显得至关重要。现有的质量分析方法多从测距误差、仪器安装误差和数据处理误差方面出发,虽然可以在一定程度上改化数据,但在如何快速定位出分层路段以及复杂城区道路纠正方面缺乏深入研究。城区交通状况复杂、高楼林立以及树木密集等不利条件影响数据精度,因此文中研究三维点云数据分层路段快速定位方法以及分层点云纠正技术,以提升点云数据精度与质量。试验结果表明该方法能够快速定位到质量不佳的路段,研究成果可为复杂城区环境下点云数据质量提升提供一定借鉴。

Experimental study of the location and data correction of layered road section for point cloud in vehicle laser scanning in complex urban area

High precision point cloud data of vehicle is the premise of extracting various urban features.However,the precision of point cloud data in urban environment is strongly degraded by man-made and natural objects that obstruct satellite signals.Therefore,how to control the quality of point cloud data in complex environment is very important.The existing quality control methods mostly start from ranging error,instrument installation error and data processing error.Although the data can be modified to a certain extent,there is a lack of in-depth study on how to quickly locate the layered road sections and the road correction in complex urban areas.In view of the data accuracy problems caused by the complex traffic conditions,high-rise buildings and dense trees,this paper focuses on the three-dimensional point cloud data hierarchical road section rapid positioning method and point cloud data correction technology,in order to achieve the purpose of improving the point cloud data accuracy and quality assurance.The experimental result shows that this method can quickly locate the poor quality road section,and the research result can provide some reference for improving the quality of point cloud data in complex urban environment.