PROGRESS IN GEOGRAPHY ›› 2018, Vol. 37 ›› Issue (6): 781-789.doi: 10.18306/dlkxjz.2018.06.005

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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

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