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

Kui Ying, Lin Ha, Yaohua Kuang and Jinhong Ding ()
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Kui Ying: Population Institute, East China Normal University, Shanghai 200241, China
Lin Ha: School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Yaohua Kuang: Population Institute, East China Normal University, Shanghai 200241, China
Jinhong Ding: Population Institute, East China Normal University, Shanghai 200241, China

Land, 2024, vol. 13, issue 9, 1-18

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.

Keywords: population distribution; spatial pattern evolution; GeoDetector; standard deviation ellipse (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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