摘要
道路网空间分布模式识别对制图综合、空间数据多尺度表达及空间数据匹配具有重要意义。城市中心是道路网语义模式的研究内容之一,通常位于道路网分布的密集区。针对现有方法存在的问题,提出一种基于道路核密度的城市几何中心识别方法。首先根据核密度估计得到道路线的连续密度分布表面;接着根据核密度统计值提取初始中心,将初始中心分为全局中心、局部中心和伪中心3类,通过面积阈值和包含关系去除伪中心;最后计算各中心区的中心力指标,并据此划分全局中心和局部中心。长春市和西安市道路网的实验结果表明,该方法识别的城市中心能够反映城市空间格局的整体特征和局部特征,与规划中心的对比结果验证了该方法的有效性。
Spatial pattern recognition of road networks is significant to cartographic generalization, multi-scale representation and spatial data matching. As one of the research contents of the road network semantic pattern, the city centers are usually located in dense areas of the road networks. In order to solve the problems in the existing methods, a city center recognition approach based on kernel density of road line is proposed in this study. Firstly, the continuous density surface of the road is generated by kernel density estimation. Then the city centers are delineated by contours based on the statistics of the density values. The centers are divided into three categories, called as global centers, local centers and fake centers respectively. The fake centers are removed according to area threshold and spatial relationship. Finally, the global centers and local centers are classified by central force index. Taking the road network data of Changchun city and Xi’an city as examples, the recognition results can reflect the overall and local characteristics of the spatial distribution pattern of the city. Besides,the overlapped degree of recognized centers and planning centers shows the effectiveness of this method.
作者
崔晓杰
巩现勇
葛文
徐振强
CUI Xiaojie;GONG Xianyong;GE Wen;XU Zhenqiang(Information Engineering University, Zhengzhou 450001, China;College of Information Science and Technology, Henan University of Technology, Zhengzhou 450001, China)
出处
《测绘科学技术学报》
北大核心
2019年第2期190-195,共6页
Journal of Geomatics Science and Technology
基金
国家自然科学基金项目(41801396)
关键词
道路网
空间分布模式
城市中心
核密度
中心力
road networks
spatial pattern
city center
kernel density
center force
