Population evolution at the prefecture-level city scale in China: Change patterns and spatial correlations

被引:0
|
作者
Yue Xian
Mingxing Chen
机构
[1] CAS,Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research
[2] University of Chinese Academy of Sciences,College of Resource and Environment
来源
关键词
population distribution; agglomeration and decentralization; pattern change; nearby urbanization; prefecture-level city;
D O I
暂无
中图分类号
学科分类号
摘要
China has entered a new stage of high-quality urbanization. Therefore, it is critical to grasp the latest population distribution and dynamics. Using mean-variance grading, Moran’s index, and the Theil index, this study compared the differences in population changes between 2010–2020 and 2000–2010 at the prefecture-level city scale based on census data to analyze the new trends in population evolution. We found that: (1) New growth poles of the population are inland provincial capitals, forming rapid-growing zones together with coastal urban agglomerations. Population growth in over 60% of the cities in the northern coastal urban agglomeration has slowed. (2) The scope of population loss in inland areas is constantly expanding. In the northeastern part of China, 92.7% of the cities have lost population, making this a typical population loss area. (3) Population shrinkage in the northeastern region and growth in the Pearl River Delta urban agglomeration show diffusion characteristics, while population patterns around the provincial capital are in a polarized stage. (4) The Theil index of population distribution increased, with 83.91% of differences coming from between groups, indicating that the gap between cities of different sizes has further expanded. This study provides scientific support for the coordinated promotion of nearby and remote urbanization.
引用
收藏
页码:1281 / 1296
页数:15
相关论文
共 50 条
  • [21] Modeling China's Prefecture-Level Economy Using VIIRS Imagery and Spatial Methods
    Cao, Jiping
    Chen, Yumin
    Wilson, John P.
    Tan, Huangyuan
    Yang, Jiaxin
    Xu, Zhiqiang
    REMOTE SENSING, 2020, 12 (05)
  • [22] The scale boundary of urbanized population with peaking PM2.5 concentration: a spatial panel econometric analysis of China's prefecture-level and above cities
    Wang, Yongpei
    Xu, Zhenyu
    JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT, 2022, 65 (01) : 126 - 149
  • [23] Study on carbon emission in prefecture-level cities of China
    Feng, Ying
    Cai, Bofeng
    High Technology Letters, 2012, 18 (01) : 101 - 106
  • [25] Spatial spillover effects and tourism-led growth: an analysis of prefecture-level cities in China
    Jiao, Shitai
    Gong, Weijin
    Zheng, Yanqiao
    Zhang, Xiaoqi
    Hu, Senlin
    ASIA PACIFIC JOURNAL OF TOURISM RESEARCH, 2019, 24 (07) : 725 - 734
  • [26] Spatial Externalities and Regional Income Inequality: Evidence from China's Prefecture-Level Data
    Liu, Xiuyan
    Yin, Xingmin
    FRONTIERS OF ECONOMICS IN CHINA, 2010, 5 (02) : 325 - 338
  • [27] Spatial-Temporal Evolution and Influencing Factors of Urban Green and Smart Development Level in China: Evidence from 232 Prefecture-Level Cities
    Xu, Lingyan
    Wang, Dandan
    Du, Jianguo
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (07)
  • [28] Urban spatial structure and environmental efficiency: Empirical analysis from prefecture-level cities in China
    Ye, Jing
    Wei, Feng
    Liu, Xihe
    Li, Jinkai
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [29] Prefecture-level health risk assessment for hot extremes in China
    Huang, Junwang
    Shen, Shi
    Cheng, Changxiu
    Song, Changqing
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2024, 108
  • [30] Exploring the effect of city size on carbon emissions: Evidence from 259 prefecture-level cities in China
    Wang, Yanan
    Liu, Jiaxin
    Wang, Juan
    Liu, Zengming
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (36) : 86165 - 86177