运用Delaunay三角网提取OpenStreetMap主干道多边形

众源开放街道地图(OpenStreetMap，OSM)作为志愿者地理信息的典型代表，其数据质量制约了城市主干道提取。为此，引入约束Delaunay三角网，运用类似Voronoi图的空间等剖分几何构造表达道路线密度，通过线密度变化与三角形边长表征主干道形态特征，并集成两个指标构建主干道识别模型；类比林火蔓延扩展过程，提出了基于Delaunay三角网的OSM主干道多边形提取方法。运用5个城市的OSM数据进行实验，结果表明，该方法能有效提取主干道多边形，并且与OSM路网中的道路等级属性趋于一致。

Extracting Arterial Road Polygon from OpenStreetMap Data Based on Delaunay Triangulation

The data quality problems of OpenStreetMap(OSM) data, which is a typical kind of volunteered geographic information data, restrict the extraction of arterial road. Firstly, this paper presents a method to identify the morphological feature of arterial road through calculating road line density change rate and length of edges using Delaunay triangulation. Then the arterial road boundary identification model is established by integrating the two control conditions with different geometric dimensions. Finally, similar to forest fire spreading, a method of extraction arterial road polygon is proposed using Delaunay triangulation. An experiment based on OSM road data of 5 cities shows that this method achieves good and effective arterial road extraction results. Furthermore, a comparison analysis of roads attribute is also carried out to confirm the consistency between constructed road levels and experiment results.