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.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Christaller W, 1933. Central Place in Southern Germany. Baskin C W trans., 1966. Englewood Cliffs. NJ and London: Prentice Hall.
Fang D C, Sun M Y, 2015. Influence of core cities in Yangtze River Economic Belt. Economic Geography, 35(1): 76–81, 20. (in Chinese)
Feng X H, Zhong Y X, Li Z R et al., 2017. Evolvement of spatial pattern of urban system in the economic belt of Yangtze River. Resources and Environment in the Yangtze Basin, 26(11): 1721–1733. (in Chinese)
Gao J Z, Zheng H W, Liu Y Z, 2018. Diagnosis of the multi-functionality of land use based on an entropy weight TOPSIS model. Resources and Environment in the Yangtze Basin, 27(11): 2496–2504. (in Chinese)
Henri L, 1966. The Sociology of Marx. Norbert G trans., 1968. New York: Columbia University Press.
Henri L, 1970. The Urban Revolution. Robert B trans., 2003. Twin Cities: University of Minnesota Press.
Hong H K, Liao H P, Wei C F et al., 2015. Health assessment of a land use system used in the ecologically sensitive area of the Three Gorges Reservoir Area, based on the improved TOPSIS method. Acta Ecologica Sinica, 35(24): 8016–8027. (in Chinese)
Irwin M D, Hughes H L, 1992. Centrality and the structure of urban interaction: Measures, concepts, and applications. Social Forces, 71(1): 17–51.
Jin G, Chen K, Wang P et al., 2019. Trade-offs in land-use competition and sustainable land development in the North China Plain. Technological Forecasting and Social Change, 141: 36–46.
Jin G, Deng X Z, Chu X et al., 2017. Optimization of land-use management for ecosystem service improvement: A review. Physics and Chemistry of the Earth, 101: 70–77.
Jin G, Deng X Z, Zhao X D et al., 2018. Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014. Journal of Geographical Sciences, 28(8): 1113–1126.
Jin G, Li Z H, Deng X Z et al., 2018. An analysis of spatiotemporal patterns in Chinese agricultural productivity between 2004 and 2014. Ecological Indicators, 105: 591–600.
Lei X P, Robin Q, Liu Y, 2016. Evaluation of regional land use performance based on entropy TOPSIS model and diagnosis of its obstacle factors. Transactions of the Chinese Society of Agricultural Engineering, 32(13): 243–253. (in Chinese)
Li D, You Y N, Ma C F et al., 2018. Analysis on the differentiation characteristics of spatial poverty and its influencing factors in the oasis towns of arid areas: Taking three south Xinjiang districts as an example. World Regional Studies, 27(3): 89–101. (in Chinese)
Li S C, Bing Z L, Jin G, 2019. Spatially explicit mapping of soil conservation service in monetary units due to land use/cover change for the Three Gorges Reservoir Area, China. Remote Sensing, 11(4): 468.
Lu C Y, Wen F, Yang Q Y et al., 2011. An evaluation of urban land use performance based on the improved TOPSIS method and diagnosis of its obstacle indicators: A case study of Chongqing. Resources Science, 33(3): 535–541. (in Chinese)
Luo M, 2017. Research on urban centricity of Yangtze River’s Midstream Urban Agglomeration [D]. Wuhan: Central China Normal University. (in Chinese)
Ma X Y, Shao J A, Xu X L, 2016. Rural transportation accessibility in mountainous areas based on the entropy-weight TOPSIS method: A case study of Shizhu County, Chongqing Municipality. Progress in Geography, 35(9): 1144–1154. (in Chinese)
Marshall J U, 1989. The Structure of Urban Systems. Toronto: University of Toronto Press.
Ning Y M, Yan Z M, 1993. The uneven development and spatial diffusion of Chinese central cities. Acta Geographica Sinica, 48(2): 97–104. (in Chinese)
Peng D Y, Xiao R J, Wang J et al., 2016. The competitiveness evaluation for the cities in the Yangtze River Economic Belt based on factor analysis. Journal of Nanchang University (Natural Science), 40(1): 97–102. (in Chinese)
Phillip B, 1987. Power and centrality: A family of measures. American Journal of Sociology, 92(5): 1170–1182.
Preston R E, 1970. Two centrality models. Yearbook of Association of Pacific Coast Geographers, 32: 59–78.
Ren L, Zhang H T, Wei M Z et al., 2019. Research on the evaluation of development level of smart city based on Entropy TOPSIS Model. Information Studies: Theory & Application, 1–12. [2019-01-05]. http://kns.cnki.net/kcms/detail/11.1762.g3.20190102.1825.002.html. (in Chinese)
Siewwuttanagul S, Inohae T, Mishima N, 2016. An investigation of urban gravity to develop a better understanding of the urbanization phenomenon using centrality analysis on GIS platform. Procedia Environmental Science, 36: 191–198.
Sun B D, Xu J H, Feng Z C, 2008. Analysis on the urban centricity and urban development of Liaoning Province. Human Geography, 23(2): 77–81. (in Chinese)
Tian M L, Liu S M, Kou Y, 2013. Evaluation on the functions of national central cities and spatial temporal evaluation of their competitiveness. City Planning Review, 37(11): 89–95. (in Chinese)
Wang Z B, Luo K, Song J et al., 2015. Characteristics of change and strategic considerations of the structure of urban functional divisions in the Yangtze River Economic Belt since 2000. Progress in Geography, 34(11): 1409–1418. (in Chinese)
Wen J, 2009. A study on the urban centricity of Wuhan Urban Circle [D]. Wuhan: Central China Normal University. (in Chinese)
Wu Y L, Liu Z D, 2010. A study on city centricity and urban development in Shandong province. Territory & Natural Resources Study, (1): 8–9. (in Chinese)
Xue L F, Ou X J, Tan H Q, 2009. Evaluation of urban centricity based on entropy method: A case study of Huaihai Economic Zone. Geography and Geo-Information Science, 25(3): 63–66. (in Chinese)
Zhang G S, Ding Z W, Xu Y M et al., 2014. Study on urban system hierarchy level structure in Henan Province: Based on the analysis of the New Urbanization Strategy of Henan Province. Areal Research and Development, 33(1): 46–51. (in Chinese)
Zhao Y, 2015. Research on the spatial poverty trap of concentrated contiguous areas with particular difficulties on basis of the geographic capital: Taking Longde County of Ningxia for example [D]. Yinchuan: Ningxia University. (in Chinese)
Zhong Y X, Feng X H, 2018. The evolution of urban functional structure from the perspective of multiscale in the Yangtze River Economic Belt. Journal of Nantong University (Social Sciences Edition), 34(1): 34–40. (in Chinese)
Zhou Y X, Zhang L, Wu Y, 2001. Study of China’s urban centrality hierarchy. Regional Areal Research and Development, 20(4): 1–5. (in Chinese)
Zou H, Duan X J, 2015. Summary reviews of studies on the Yangtze River Economic Belt. Resources and Environment in the Yangtze Basin, 24(10): 1672–1682. (in Chinese)
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation: National Natural Science Foundation of China, No.41871176; The “Hua Bo” Plan of Central China Normal University; Postgraduate Education Innovation Subsidy Project of Central China Normal University, No.2018CXZZ004
Author: Luo Jing (1966–), Professor, specialized in human geography and economic geography.
Sun Xuan (1992–), PhD, specialized in regional sustainable development and urban and rural planning.
Rights and permissions
About this article
Cite this article
Luo, J., Chen, S., Sun, X. et al. Analysis of city centrality based on entropy weight TOPSIS and population mobility: A case study of cities in the Yangtze River Economic Belt. J. Geogr. Sci. 30, 515–534 (2020). https://doi.org/10.1007/s11442-020-1740-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11442-020-1740-9