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The Factors Influencing China’s Population Distribution and Spatial Heterogeneity: Based on Multi-source Remote Sensing Data

Author

Listed:
  • Shasha Huang

    (Jiangsu University of Science and Technology)

  • Jiandong Chen

    (Southwestern University of Finance and Economics)

  • Ming Gao

    (Southwestern University of Finance and Economics)

  • Mengjiao Yuan

    (Southwestern University of Finance and Economics)

  • Zunhong Zhu

    (Nanjing Audit University)

  • Xueli Chen

    (Chinese Academy of Social Sciences)

  • Malin Song

    (Anhui University of Finance and Economics
    Anhui University of Finance and Economics
    Lebanese American University)

Abstract

Examining the factors that influence population distribution enables us to gain insights into the patterns and evolutionary trends of distribution over time. Based on the Spatial Durbin Model (SDM) with satellite data of nighttime light, net primary productivity (NPP), and the digital evaluation model (DEM), this study examines the population distribution of 303 prefecture-level cities in China between 2007 and 2017 in terms of three dimensions—economic development, ecological environment, and topography. The empirical results reveal that, firstly, the above-mentioned multiple factors have caused the current population distribution in Chinese cities. Economic development emerges as a potent force driving population concentration within local regions while simultaneously exerting a draining influence on surrounding urban centers. Secondly, the environment has a significant agglomeration effect on local regions and surrounding areas, while the average altitude can inhibit population aggregation. It is worth noting, however, that in eastern China, average altitude surprisingly contributes to population concentration within the local area.

Suggested Citation

  • Shasha Huang & Jiandong Chen & Ming Gao & Mengjiao Yuan & Zunhong Zhu & Xueli Chen & Malin Song, 2024. "The Factors Influencing China’s Population Distribution and Spatial Heterogeneity: Based on Multi-source Remote Sensing Data," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 2179-2203, October.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:4:d:10.1007_s10614-023-10515-y
    DOI: 10.1007/s10614-023-10515-y
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    References listed on IDEAS

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    1. Alperovich, Gershon, 1992. "Economic Development and Population Concentration," Economic Development and Cultural Change, University of Chicago Press, vol. 41(1), pages 63-74, October.
    2. Everett Lee, 1966. "A theory of migration," Demography, Springer;Population Association of America (PAA), vol. 3(1), pages 47-57, March.
    3. Wilson, Matthew A. & Howarth, Richard B., 2002. "Discourse-based valuation of ecosystem services: establishing fair outcomes through group deliberation," Ecological Economics, Elsevier, vol. 41(3), pages 431-443, June.
    4. Xiangzheng Deng & Jikun Huang & Scott Rozelle & Emi Uchida, 2010. "Economic Growth and the Expansion of Urban Land in China," Urban Studies, Urban Studies Journal Limited, vol. 47(4), pages 813-843, April.
    5. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    6. Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Chen, Zuoqi & Liu, Rui & Li, Linyi & Wu, Jianping, 2016. "Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis," Applied Energy, Elsevier, vol. 168(C), pages 523-533.
    7. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    8. Liguo Zhang & Langping Leng & Yongming Zeng & Xi Lin & Su Chen, 2021. "Spatial distribution of rural population using mixed geographically weighted regression: Evidence from Jiangxi Province in China," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
    9. Guangqing Chi & David Marcouiller, 2011. "Isolating the Effect of Natural Amenities on Population Change at the Local Level," Regional Studies, Taylor & Francis Journals, vol. 45(4), pages 491-505.
    10. Christopher D. Elvidge & Daniel Ziskin & Kimberly E. Baugh & Benjamin T. Tuttle & Tilottama Ghosh & Dee W. Pack & Edward H. Erwin & Mikhail Zhizhin, 2009. "A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data," Energies, MDPI, vol. 2(3), pages 1-28, August.
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