Population Distribution in Guizhou’s Mountainous Cities: Evolution of Spatial Pattern and Driving Factors

Guizhou is a typical mountainous province and is also one of the lowland regions in China that has attracted a population influx. Here, using population density data from 2000 to 2020 as the basic dataset and the coefficient of variation method and standard deviation ellipse analysis, we investigated the spatial characteristics across different years. The results show: Firstly, Guizhou’s population has a distinct spatial distribution, characterized by a lower population density in the southeast and a higher density in the northwest as well as an increasing polarization of population concentration toward the centers of prefecture-level cities and provincial capitals. Fluctuations in population density resemble a central siphon effect, which is particularly pronounced in the provincial capital and show a significant gravitational pull. Secondly, the coefficient of variation in population density across Guizhou’s counties is spatially divided by Guiyang, showing higher values in the east and lower values in the west. Furthermore, the ellipse of the standard deviation of population density is gradually shrinking, indicating an increasingly concentrated population distribution. Thirdly, the explanatory power of the population and socio-economic systems on the population distribution in Guizhou is significantly greater than that of the natural systems. Population distribution and migration patterns have shifted from purely “economic driven” to coexisting with “economic and comfort-oriented” trends, and there is an urgent need to improve the comfort level of public services as a typical supply, in order to boost Guizhou’s population attraction.

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Publication Details

Journal
Land
Published
2024-09-10
DOI
https://doi.org/10.3390/land13091469
Citations
2
Primary Topic
Regional Economic and Spatial Analysis
Type
article
Field-Weighted Citation Impact
2.26

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article

Population Distribution in Guizhou’s Mountainous Cities: Evolution of Spatial Pattern and Driving Factors

Lin Ha, Kui Ying, Jinhong Ding, Yaning Kuang
2 citations
Land
Regional Economic and Spatial Analysis
2.26
article

Population Distribution in Guizhou’s Mountainous Cities: Evolution of Spatial Pattern and Driving Factors

Lin Ha, Kui Ying, Jinhong Ding, Yaning Kuang
article en
2 citations

Abstract

Guizhou is a typical mountainous province and is also one of the lowland regions in China that has attracted a population influx. Here, using population density data from 2000 to 2020 as the basic dataset and the coefficient of variation method and standard deviation ellipse analysis, we investigated the spatial characteristics across different years. The results show: Firstly, Guizhou’s population has a distinct spatial distribution, characterized by a lower population density in the southeast and a higher density in the northwest as well as an increasing polarization of population concentration toward the centers of prefecture-level cities and provincial capitals. Fluctuations in population density resemble a central siphon effect, which is particularly pronounced in the provincial capital and show a significant gravitational pull. Secondly, the coefficient of variation in population density across Guizhou’s counties is spatially divided by Guiyang, showing higher values in the east and lower values in the west. Furthermore, the ellipse of the standard deviation of population density is gradually shrinking, indicating an increasingly concentrated population distribution. Thirdly, the explanatory power of the population and socio-economic systems on the population distribution in Guizhou is significantly greater than that of the natural systems. Population distribution and migration patterns have shifted from purely “economic driven” to coexisting with “economic and comfort-oriented” trends, and there is an urgent need to improve the comfort level of public services as a typical supply, in order to boost Guizhou’s population attraction.

LandVol. 13(9)
East China Normal University (CN)
East China Normal University
Openalex Percentile: Top 8%
Regional Economic and Spatial Analysis
2.26
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