Xiaohan Zhao
College of Geography and Environment, Shandong Normal University, Jinan, Shandong, 250358, China
Yanbin Chen
College of Geography and Environment, Shandong Normal University, Jinan, Shandong, 250358, China
Population density functions have long been used to describe the spatial structure of regional population distributions. Several studies have been conducted to examine the population distribution in Shandong Province, China, but few have applied regional density functions to the analysis. Therefore, based on the 2000, 2010, and 2020 population censuses, this study used monocentric and polycentric regional density functions to study the characteristics of population agglomeration and diffusion in Shandong. This is followed by an in-depth discussion based on population growth rate data and hot- and cold-spot analyses. The results showed that the Shandong Province population was spatially unevenly distributed. Population growth rates were higher in urban centers and counties, with more significant changes in population size in the eastern coastal areas than in the inland areas. As verified in this study, the logarithmic form of the single-center regional density function R2 was greater than 0.8, which was in line with the population spatial structure of Shandong Province. During the study period, the estimated population density of the regional center and the absolute value of the regional population density gradient both increased, indicating a clear and increasing trend of centripetal agglomeration of regional centers over the study period. Overall, the R2 value of the multicenter region density function was higher than that of the single-center region density function. The polycentric regional density function showed that the population density gradient of some centers had a downward trend, which reflected the spatial development trend of outward diffusion in these centers. Meanwhile, the variation in the estimated population density and the population density gradient exhibited differences in the central population distribution patterns at different levels.
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Copyright © 2023 Xiaohan Zhao, Yanbin Chen
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