摘要
常规的矢量地图精度校验采用抽样与实地测量,外业工作量大,自动化程度低。针对这一问题,本文提出基于SSW激光点云数据的矢量地图平面精度自动校验方法。首先,使用车载激光扫描器获得道路两侧高精度点云数据,并对点云数据进行滤波、坐标转换和精度检验;其次,基于多特征识别算法,使用SWDY软件提取点云特征点线;最后,利用最近邻法搜索待检矢量图中的同类地物特征点线,并计算匹配点线对的中误差。以兴化城区为试验区,采用该方法检测该地区1∶1000比例尺的矢量地图平面精度,试验结果显示,成功匹配了点云数据205个地物特征中的201个,矢量地图的总体中误差为0.26 m,且能够发现待检测矢量地图中的采集丢漏与明显错误。本文方法可以减少现有检测方法的野外实测工作量,增加检测样本数量,降低检测过程中的人为干扰因素,有效提升检测的可靠性与检测效率。
Routine calibration of vector maps is based on sampling and field measurement,with much workload and low automation. To solve this problem,automatic calibration method for vector map plane accuracy based on SSW laser point cloud data is presented. First of all,the vehicle laser scanner is used to obtain the high precision point cloud data on both sides of the road. The point cloud data is filtered,transformed coordinate and verified accuracy. Secondly,based on multi-feature recognition algorithm,SWDY software is used to extract point cloud feature points. Finally,the nearest neighbor method is used to search the same class of featured points and line,the mean square error of matched points and line is calculated. This method is used to verify plane accuracy of vector map with 1 ∶ 1000 measuring scale in Xinghua city. The experimental results show that 201 of the 205 feature features of the point cloud data are successfully matched. The overall error of the vector map is 0.26 m,and the acquisition and leakage and the obvious error in the vector map can be found. The method can reduce the field workload of existing detection methods,increase the quantity of testing sample,and lower human disturbance factors in the process of detection,which effectively improve the reliability and efficiency of detection.
作者
羌鑫林
李广伟
王留召
张伟红
QIANG Xinlin;LI Guangwei;WANG Liuzhao;ZHANG Weihong(Jiangsu Provincial Surveying and Mapping Engineering Institute, Nanjing 210013, China;Chinese Academy of Surveying and mapping, Beijing 100039, China;Faculty of Geomatics, Kunming Metallurgy College, Kunming 650033, China)
出处
《测绘通报》
CSCD
北大核心
2019年第3期98-102,共5页
Bulletin of Surveying and Mapping
基金
国家自然科学基金(41371434
41771491)
关键词
激光点云
点云识别
矢量地图
自动匹配
平面精度
laser point cloud
point cloud recognition
vector map
automatic matching
plane accuracy
作者简介
羌鑫林(1983-),男,硕士,高级工程师,主要研究方向为数字城市、移动测量。E-mail:qiangxinlin@163.com;通讯作者:张伟红。E-mail:348318031@qq.com.
