针对矢量道路网的变化检测与更新问题,提出一种基于大规模浮动车轨迹点数据的道路网快速变化发现与更新方法。首先对矢量道路网进行栅格化处理,并根据若干天内浮动车GPS轨迹点落在栅格内的个数对栅格赋值。经过对轨迹栅格图像的低通滤波、边界清理后,采用数学形态学方法提取轨迹栅格图像的骨架线,通过判断道路骨架线与更新前道路网缓冲区之间的位置关系,快速识别出变化道路,即新增道路和消失道路。最后,对更新道路的骨架线分别进行剪枝处理、断线连接以及节点融合,实现对原有道路网道路数据的提示性更新。结果表明:与传统方法相比,该方法能够以更低的成本和更好的现势性对现有道路网进行在线增量式快速变化检测和更新。
Aiming at continued and timely map update of vector road network,this paper realizes an automated change detection and suggestive update of vector road network by analyzing crowdsourcing spatial data-large scale floating car GPS data.The method proposed in this paper firstly rasterize vector road network map by setting aproper grid size,and then assign a value to every pixel according to the count which several days of GPS track points are fall within grid,and final binarized road image can be obtained by further low pass filtering and boundary cleaning.Secondly,skeleton lines of road raster collection which correspond to vector road centerlines can be extracted by means of Mathematical Morphology,and road change including new roads,modified roads and missing roads can be quickly detected by comparing the spatial relationship between road raster area where road skeleton line lie in and buffer area of the existing road centerline.At last,after trimming,merging and connecting the broken skeleton line,skeleton lines,as the updated road centerlines,can be merged into the existing road network finally.