面向道路网VGI数据的匹配与融合方法

摘要

Volunteered Geographic Information(VGI)is an emerging geographic data collection method with the advantages of fast update,rich detail and wide coverage,etc.VGI can be used to update road networks quickly.However,VGI data is shared and collected by non-professional volunteers,which causes a poor data quality.But a large number of VGI data repeatedly collected and fused on the same geographical elements can improve the quality of the data.This paper takes the road network data collected by many people as an example,and combines feature vector matching and fusion theory.On this basis,the research designs a matching and fusion algorithm for VGI data of road network.First,a buffer is established at the road node,and the node matching is carried out by using the road node similarity.Then the road is matched according to the road distance similarity.Finally,the Delaunay triangulation fusion algorithm is used to fuse the matched roads and get a new road network.In order to evaluate the fusion performance,the original VGI road networks and Google Earth images are used to compare with the new road network.The result shows that the proposed algorithm can effectively realize the matching and fusion of VGI data of road network.%自发地理信息(VGI)是一种新兴的地理数据采集方式,具有数据更新快、细节丰富、覆盖范围广等优势.利用VGI数据可以对道路网实现快速更新;但是由于VGI数据是非专业自发共享的,且数据采集时多使用非专业设备,所以存在数据质量不高的问题.大量VGI数据对同一地理要素的重复采集与融合处理则可改善数据的质量,文中以多人采集的道路网数据为例,结合矢量要素的匹配与融合理论,设计一种适用于道路网VGI数据的匹配与融合算法.首先在路段结点处建立缓冲区进行结点匹配,再根据路段距离相似度进行路段匹配,最后再利用Delaunay三角剖分融合算法对匹配后的同名路段进行融合.将匹配融合后的道路网与原始道路网 VGI数据及Google影像图叠加对比分析,结果表明利用本文算法可有效地实现道路网VGI数据的匹配与融合.