Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/12/7/1350 |
| _version_ | 1797588611062824960 |
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| author | Fan Li Jie Zhou Wei Wei Li Yin |
| author_facet | Fan Li Jie Zhou Wei Wei Li Yin |
| author_sort | Fan Li |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T00:54:29Z |
| format | Article |
| id | doaj.art-21e869c9a3ee4632b9184da0521eea16 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-11T00:54:29Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-21e869c9a3ee4632b9184da0521eea162023-11-18T20:06:10ZengMDPI AGLand2073-445X2023-07-01127135010.3390/land12071350Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census DataFan Li0Jie Zhou1Wei Wei2Li Yin3Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, ChinaDepartment of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, ChinaDepartment of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, ChinaDepartment of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, ChinaUnderstanding 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.https://www.mdpi.com/2073-445X/12/7/1350spatial agingelderly populationspatial distributionspatial evolutionWuhan |
| spellingShingle | Fan Li Jie Zhou Wei Wei Li Yin Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data Land spatial aging elderly population spatial distribution spatial evolution Wuhan |
| title | Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data |
| title_full | Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data |
| title_fullStr | Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data |
| title_full_unstemmed | Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data |
| title_short | Spatial Distribution Pattern and Evolution Characteristics of Elderly Population in Wuhan Based on Census Data |
| title_sort | spatial distribution pattern and evolution characteristics of elderly population in wuhan based on census data |
| topic | spatial aging elderly population spatial distribution spatial evolution Wuhan |
| url | https://www.mdpi.com/2073-445X/12/7/1350 |
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