Spatial and temporal changes in population distribution and population projection at county level in China
Mei Sang,
Jing Jiang (),
Xin Huang,
Feifei Zhu and
Qian Wang
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Mei Sang: Gansu Agricultural University
Jing Jiang: Gansu Agricultural University
Xin Huang: Gansu Agricultural University
Feifei Zhu: Gansu Agricultural University
Qian Wang: Gansu Agricultural University
Palgrave Communications, 2024, vol. 11, issue 1, 1-13
Abstract:
Abstract Counties in China play a pivotal role in economic and social development, acting as essential leadership hubs for large and medium-sized cities, contributing to rural revitalization, and facilitating urban-rural integration. Using ArcGIS spatial analysis, this study examines the population distribution spatial and dispersion patterns in Chinese counties based on 40 years of data from the first to the seventh national population census. Results reveal noticeable growth trends and regional disparities in county populations, with an increase in large-population counties and a decrease in small-population ones. Recent population growth concentrates in urban agglomerations, metropolitan areas, and southeastern coastal regions, while reductions occur in the northeastern and Inner Mongolia border areas. Furthermore, the study identifies “high-high” agglomerations around provincial capitals and “low-low” agglomerations in economically underdeveloped western and northeastern border regions. China’s population distribution spatial agglomeration has been increasing, with acceleration toward specific areas. The first through seventh census show rapid growth at low density, followed by growth at medium density, stable growth, and eventually negative growth. This suggests a likely slowdown and potential reversal in China’s future population growth. Additionally, an Auto Regression Integrated Moving Average (ARIMA) model is employed to forecast China’s total population, projecting a decline to 1343.68 million by 2035. The emergence of “population loss counties” in contemporary China underscores the need for a rational understanding of their development status and trends to optimize population development strategies and promote economic and social progress.
Date: 2024
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DOI: 10.1057/s41599-024-02784-1
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