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Study on Influencing Factors and Planning Strategies of Population Spatial Distribution in Urban Fringe Areas from the Perspective of Built Environment—The Case of Wuhan, China

Author

Listed:
  • Yan Long

    (School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Zhengyuan Lu

    (School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Siyu Hu

    (School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Shiqi Luo

    (School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Xi Liu

    (School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Jingmei Shao

    (School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Yuqiao Zheng

    (School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Xuejun Liu

    (School of Urban Design, Wuhan University, Wuhan 430072, China
    Research Center for Digital City, Wuhan University, Wuhan 430072, China)

Abstract

Rationally relieving the population of urban centers in large cities, such as megacities and supercities, is one of the current goals of population development in China. The fringe area of a large city is a potential area to undertake the population of the central area. Studying the relationship between the population and the built environment in this area can help urban planners formulate targeted construction strategies to attract the population of the city center to move to the fringe areas. This paper takes the fringe areas of Wuhan in 2010 and 2020 as its specific research object and puts forward the “5D” index system of built environments that affects the spatial distribution of population based on population data and built environment data. The OLS model is used to screen the influencing factors. This paper analyzes the correlation between population and built environment using a multi-scale geographic weighted regression model as well. According to the results of the regression analysis combined with the development and construction of the fringe areas of remote urban areas in Wuhan over the past 20 years, some suggestions are put forward for the planning and construction of remote urban areas. The results show that the “5D” index system of the built environment covers the influencing factors of the spatial distribution of the population. MGWR reveals the correlation between the influencing factors and the spatial distribution of population in the marginal areas on the global scale and the local scale, respectively, which provides a clear direction for the development of planning and construction to improve the attractiveness of the non-central areas to the population.

Suggested Citation

  • Yan Long & Zhengyuan Lu & Siyu Hu & Shiqi Luo & Xi Liu & Jingmei Shao & Yuqiao Zheng & Xuejun Liu, 2023. "Study on Influencing Factors and Planning Strategies of Population Spatial Distribution in Urban Fringe Areas from the Perspective of Built Environment—The Case of Wuhan, China," Land, MDPI, vol. 12(9), pages 1-35, September.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1739-:d:1235180
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    References listed on IDEAS

    as
    1. Colin Vance & Ralf Hedel, 2007. "The impact of urban form on automobile travel: disentangling causation from correlation," Transportation, Springer, vol. 34(5), pages 575-588, September.
    2. Guiyuan Li & Guo Cheng & Zhenying Wu & Xiaoxiao Liu, 2022. "Coupling Coordination Research on Disaster-Adapted Resilience of Modern Infrastructure System in the Middle and Lower Section of the Three Gorges Reservoir Area," Sustainability, MDPI, vol. 14(21), pages 1-24, November.
    3. Xin Lao & Hengyu Gu, 2020. "Unveiling various spatial patterns of determinants of hukou transfer intentions in China: A multi‐scale geographically weighted regression approach," Growth and Change, Wiley Blackwell, vol. 51(4), pages 1860-1876, December.
    4. Daniel P. McMillen, 2004. "Geographically Weighted Regression: The Analysis of Spatially Varying Relationships," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 554-556.
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    Cited by:

    1. Weiting Xiong & Junyan Yang, 2023. "Delineating and Characterizing the Metropolitan Fringe Area of Shanghai—A Spatial Morphology Perspective," Land, MDPI, vol. 12(12), pages 1-22, November.

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