地理科学进展 ›› 2018, Vol. 37 ›› Issue (6): 781-789.doi: 10.18306/dlkxjz.2018.06.005

• 研究论文 • 上一篇    下一篇

基于道路交叉点邻域扩张曲线的城市边界识别——以成都、西安、武汉、南京和长沙为例

林晓娟1,2(), 房世峰2, 徐亚莉1,3, 邹宝裕1, 罗明良1,3,*()   

  1. 1. 西华师范大学国土资源学院,四川 南充 637002
    2. 中国科学院地理科学与资源研究所,资源与环境信息系统国家重点实验室,北京 100101
    3. 西华师范大学地表过程与环境变化研究所,四川 南充 637002
  • 收稿日期:2017-04-09 修回日期:2017-08-14 出版日期:2018-06-28 发布日期:2018-06-28
  • 通讯作者: 罗明良 E-mail:lxjxiaojuan@163.com;lolean586@163.com
  • 作者简介:

    作者简介:林晓娟(1996-),女,四川成都人,本科生,主要从事GIS空间分析与应用,E-mail: lxjxiaojuan@163.com

  • 基金资助:
    国家自然科学基金项目(41101348,U1503184);中国科学院大学生创新实践训练计划项目;西华师范大学基本科研业务费专项资金资助项目(15C002);绵阳师范学院四川省生态安全与保护重点实验室资助项目(ESP1606)

Identifying urban boundaries by clustering street node based on neighborhood dilation curve:A case study of Chengdu, Xi'an, Wuhan, Nanjing and Changsha

Xiaojuan LIN1,2(), Shifeng FANG2, Yali XU1,3, Baoyu ZOU1, Mingliang LUO1,3,*()   

  1. 1. School of Land and Resources, China West Normal University, Nanchong 637002, Sichuan, China
    2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    3. Institute of Land Surface Processes and Environmental Changes, China West Normal University, Nanchong 637002, Sichuan, China
  • Received:2017-04-09 Revised:2017-08-14 Online:2018-06-28 Published:2018-06-28
  • Contact: Mingliang LUO E-mail:lxjxiaojuan@163.com;lolean586@163.com
  • Supported by:
    National Natural Science Foundation of China, No.41101348, No.U1503184;Chinese Academy of Sciences Innovation Practice Training Program for College Students;Basic Research Project Financed by the Special Fund of China West Normal University, No.15C002;Sichuan Key Laboratory of Ecological Security and Protection in Mianyang Normal College, No.ESP1606

摘要:

城市边界识别是定性和定量研究城市的基础和前提,已有的关于城市边界提取的研究大都需要提前设定阈值或依赖人口统计数据。基于分形几何学,利用矢量建筑物分布数据识别城市边界,虽可克服这一缺陷,但国内城市边界的研究往往受阻于矢量建筑物分布数据获取困难。本文提出了一种基于道路交叉点的邻域扩张曲线作为识别城市边界的新方法。结果表明:该方法以电子地图为数据源,基于道路交叉点矢量数据进行研究时,城市集群数据随搜索半径增大而改变,城市扩张曲线中的最佳距离阈值是提取城市边界的关键;提取成都、西安、武汉、南京和长沙城市边界的最佳距离阈值分别为133、114、139、124和129 m,各城市的集群面积分别为769、350、270、317和359 km2。利用道路交叉点提取城市边界,方法简便可行,数据较易获得,本文结论有望为城市形态发展演变和城市规划等相关研究提供参考。

关键词: 城市边界, 道路交叉点, 邻域扩张曲线, 曲率变点, 电子地图

Abstract:

Identifying urban boundaries is the basis of qualitative and quantitative study of cities. Most of the existing studies on the identification of urban boundaries rely on predefined distance thresholds or incorporate census data. Although fractal geometry method using building vector maps to identify urban boundaries can overcome this problem, the research of urban boundary identification in China is often hindered by the difficulty of obtaining vector building distribution data. This study draws upon existing research results and puts forward a new method to identify urban boundaries by clustering street nodes based on neighborhood dilation curves. The results show that the key to this method that uses street nodes from electronic map as data source lies in finding the optimal distance threshold corresponding to the maximum curvature. The distance threshold for extracting urban boundaries of Chengdu, Xian, Wuhan, Nanjing, and Changsha are 133, 114, 139, 124, and 129 m; and the area of city clusters are 769, 350, 270, 317, and 359 km2, respectively. The method of using street nodes vector data to identify urban boundaries is simple and feasible, and the data are easy to obtain. So the results of this study may provide some reference for the study of urban morphology, urban evolution, and urban planning.

Key words: urban boundaries, street nodes, neighborhood dilation curve, curvature inflection point, electronic map