Journal of Geographical Sciences ›› 2020, Vol. 30 ›› Issue (4): 515-534.doi: 10.1007/s11442-020-1740-9

• Special Issue: Development and Protection of Territorial Space in the Yangtze River Economic Belt •     Next Articles

Analysis of city centrality based on entropy weight TOPSIS and population mobility: A case study of cities in the Yangtze River Economic Belt

LUO Jing1,2,3, CHEN Siyun1,2,3, SUN Xuan4,*(), ZHU Yuanyuan1,2,3, ZENG Juxin1,2,3, CHEN Guangping5   

  1. 1. College of Public Administration, Central China Normal University, Wuhan 430079, China
    2. School of Management, Wuhan Institute of Technology, Wuhan 430205, China
    3. Department of Urban Planning and Design, University of Hong Kong, Hong Kong 999077, China
    4. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    5. School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
  • Received:2019-04-25 Accepted:2019-12-29 Online:2020-04-25 Published:2020-06-25
  • Contact: SUN Xuan E-mail:muxuan0524@126.com
  • About author:Luo Jing (1966-), Professor, specialized in human geography and economic geography. E-mail: luojing@mail.ccnu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(41871176);The “Hua Bo” Plan of Central China Normal University;Postgraduate Education Innovation Subsidy Project of Central China Normal University(2018CXZZ004)

Abstract:

Based on statistical data and population flow data for 2016, and using entropy weight TOPSIS and the obstacle degree model, the centrality of cities in the Yangtze River Economic Belt (YREB) together with the factors influencing centrality were measured. In addition, data for the population flow were used to analyze the relationships between cities and to verify centrality. The results showed that: (1) The pattern of centrality conforms closely to the pole-axis theory and the central geography theory. Two axes, corresponding to the Yangtze River and the Shanghai-Kunming railway line, interconnect cities of different classes. On the whole, the downstream cities have higher centrality, well-defined gradients and better development of city infrastructure compared with cities in the middle and upper reaches. (2) The economic scale and size of the population play a fundamental role in the centrality of cities, and other factors reflect differences due to different city classes. For most of the coastal cities or the capital cities in the central and western regions, factors that require long-term development such as industrial facilities, consumption, research and education provide the main competitive advantages. For cities that are lagging behind in development, transportation facilities, construction of infrastructure and fixed asset investment have become the main methods to achieve development and enhance competitiveness. (3) The mobility of city populations has a significant correlation with the centrality score, the correlation coefficients for the relationships between population mobility and centrality are all greater than 0.86 (P<0.01). The population flow is mainly between high-class cities, or high-class and low-class cities, reflecting the high centrality and huge radiating effects of high-class cities. Furthermore, the cities in the YREB are closely linked to Guangdong and Beijing, reflecting the dominant economic status of Guangdong with its geographical proximity to the YREB and Beijing’s enormous influence as the national political and cultural center, respectively.

Key words: city centrality, entropy weight TOPSIS, population mobility, Yangtze River Economic Belt, obstacle degree model