PROGRESS IN GEOGRAPHY ›› 2019, Vol. 38 ›› Issue (12): 1957-1967.doi: 10.18306/dlkxjz.2019.12.011

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Measuring polycentric urban structure using Easygo big data: A case study of Chongqing metropolitan area

DUAN Yaming1, LIU Yong2,*(), LIU Xiuhua3, HE Dong3   

  1. 1. College of Land Science and Technology, China Agricultural University, Beijing 100193, China
    2. School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China
    3. College of Resources and Environment, Southwest University, Chongqing 400715, China
  • Received:2018-12-12 Revised:2019-06-26 Online:2019-12-28 Published:2019-12-28
  • Contact: LIU Yong
  • Supported by:
    National Natural Science Foundation of China(41771534)


Polycentricity has become the spatial development strategy in many Chinese cities. Effective identification of polycentric urban form is of great significance for assessing planning performance and formulating better planning strategy. Compared with Baidu Heat Map and cell phone call data, Tencent Easygo data have the advantages of high spatial and temporal resolution and low acquisition cost, which can be used to compare the population agglomeration capabilities of different urban centers, and dynamically identify and monitor polycentric urban form. Taking Chongqing metropolitan area as an example, this study applied the method of Kernel density analysis to identify its polycentric urban form and the size and rank of the urban centers based on Tencent Easygo data of one week. The results show that Chongqing as a mountainous city has developed a polycentric urban structure with multiple subcenters and urban clusters due to the constraint of natural environment, the drive of economic forces, and the guidance of urban planning. The main center and several subcenters inside the inner ring road have comparable degrees of population aggregation, land use scales, and urban development levels. These subcenters are also stronger than the other subcenters outside the inner ring road. The study pointed out that the urban development degree and population aggregation capacity of Xiyong, Chayuan, and peripheral urban clusters need to be improved.

Key words: urban spatial structure, polycentric form, Easygo data, Chongqing