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The Factors Influencing China’s Population Distribution and Spatial Heterogeneity: a Prefectural-Level Analysis using Geographically Weighted Regression

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Abstract

The study of population distribution and its influencing factors is one of the key fields within population geography. Most previous studies have used traditional global regression models to explore the factors influencing population distribution, but they neglect spatial heterogeneity. To overcome this weakness, we employed the Geographically Weighted Regression (GWR) model to identify spatially varying relationships between population density and potential influencing factors in mainland China. The results showed that road density, GDP, temperature and arable land proportion were the key factors influencing population distributions and that the influence of each factor varied in different regions. A lower road density significantly restricted population agglomeration in less developed regions such as Southwest China. The regression coefficients of GDP decreased from the more developed Southeast China to the less developed Northwest China. The regression coefficients of temperature were higher in southeastern coastal areas. Arable land proportion was a significant factor increasing population agglomeration in Xinjiang, Northwest China, but this relationship was weaker in other parts of China. We argue that regional population and development policy should be made according to the specific factors crucially influencing population distributions in various regions in order to promote orderly immigration and optimize population distribution.

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Notes

  1. According to this strategy, Beijing will transfer its non-capital functions, such as general manufacturing, downtown wholesale markets as well as some educational and medical services, to Tianjin and Hebei; guide the immigrant population out of Beijing and ease the big city disease; and promote regional coordinated development.

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Acknowledgements

We would like to thank RESDC (Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences) and CNERN (The Chinese National Ecosystem Research Network) for the providing of datasets. We are also grateful for the excellent suggestions and comments from the editor, two anonymous referees, Dr. Rui Li, Dr. Cassandra C. Wang and Dr. Yehua Dennis Wei.

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  1. Zhejiang University, Zhejiang, China

    Zhibin Xu & Anjiao Ouyang

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Xu, Z., Ouyang, A. The Factors Influencing China’s Population Distribution and Spatial Heterogeneity: a Prefectural-Level Analysis using Geographically Weighted Regression. Appl. Spatial Analysis 11, 465–480 (2018). https://doi.org/10.1007/s12061-017-9224-8

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