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Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data

Author

Listed:
  • Fan Li

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

  • Jie Zhou

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

  • Wei Wei

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China
    China Institute of Development Strategy and Planning, Wuhan University, Wuhan 430072, China)

  • Li Yin

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

Abstract

Understanding the spatial distribution pattern and evolution characteristics of the elderly population in urban areas is of great significance for the development of urban planning and the implementation of public management policies in the context of rapid aging. Accurately identifying the spatial distribution and evolution characteristics of the elderly population in a city requires a comprehensive analysis of multiple indicators and large-scale data. Taking Wuhan City as an example, this article measures the spatial distribution characteristics and evolution trend of the elderly population from 2000 to 2020 at the street/township level based on data from the fifth, sixth, and seventh censuses, using methods such as kernel density hotspot detection, spatial clustering analysis, and standard deviation ellipse analysis. The results show that (1) there are significant differences in the aging spatial pattern between the central area and the suburban areas of Wuhan; (2) overall, Wuhan’s aging rate shows a typical “core–periphery” growth mode in space, while the density of the elderly population has significant spatial aggregation characteristics and shows an evolution trend of “centralized concentration, peripheral outliers, axial development, and near-field growth”; (3) the center of gravity of the elderly population remains relatively stable over time.

Suggested Citation

  • Fan Li & Jie Zhou & Wei Wei & Li Yin, 2023. "Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data," Land, MDPI, vol. 12(7), pages 1-16, July.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:7:p:1350-:d:1188178
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    References listed on IDEAS

    as
    1. Ke Zhang & Hao Sun & Xiangyu Li, 2022. "Aging Population Spatial Distribution Discrepancy and Impacting Factor," Sustainability, MDPI, vol. 14(15), pages 1-22, August.
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    Cited by:

    1. Xiaoxiang Tang & Cheng Zou & Chang Shu & Mengqing Zhang & Huicheng Feng, 2024. "Research on Site Selection Planning of Urban Parks Based on POI and Machine Learning—Taking Guangzhou City as an Example," Land, MDPI, vol. 13(9), pages 1-18, August.
    2. Kui Ying & Lin Ha & Yaohua Kuang & Jinhong Ding, 2024. "Population Distribution in Guizhou’s Mountainous Cities: Evolution of Spatial Pattern and Driving Factors," Land, MDPI, vol. 13(9), pages 1-18, September.
    3. Huicheng Feng & Xiaoxiang Tang & Cheng Zou, 2024. "Optimizing the Layout of Service Facilities for Older People Based on POI Data and Machine Learning: Guangzhou City as an Example," Land, MDPI, vol. 13(5), pages 1-15, May.

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