IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v64y2024i4d10.1007_s10614-023-10515-y.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-023-10515-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-023-10515-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    8. 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.
    9. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei Chen & Rui He & Qun Wu, 2017. "A Novel Efficiency Measure Model for Industrial Land Use Based on Subvector Data Envelope Analysis and Spatial Analysis Method," Complexity, Hindawi, vol. 2017, pages 1-11, December.
    2. Zhao, Mingxuan & Lv, Lianhong & Wu, Jing & Wang, Shen & Zhang, Nan & Bai, Zihan & Luo, Hong, 2022. "Total factor productivity of high coal-consuming industries and provincial coal consumption: Based on the dynamic spatial Durbin model," Energy, Elsevier, vol. 251(C).
    3. Jianzhong Xu & Bingjun Tong & Manman Wang & Shi Yin, 2024. "Does environmental pollution governance contribute to carbon emission reduction under heterogeneous green technological innovation? Empirical evidence from China’s provincial panel data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(12), pages 31727-31756, December.
    4. Haller, Peter & Heuermann, Daniel F., 2016. "Job search and hiring in local labor markets: Spillovers in regional matching functions," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 125-138.
    5. John Gibson & Chao Li & Geua Boe-Gibson, 2014. "Economic Growth and Expansion of China’s Urban Land Area: Evidence from Administrative Data and Night Lights, 1993–2012," Sustainability, MDPI, vol. 6(11), pages 1-16, November.
    6. Sheng, Jichuan & Qiu, Wenge, 2022. "Water-use technical efficiency and income: Evidence from China's South-North Water Transfer Project," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    7. Hu, Ting & Huang, Xin, 2019. "A novel locally adaptive method for modeling the spatiotemporal dynamics of global electric power consumption based on DMSP-OLS nighttime stable light data," Applied Energy, Elsevier, vol. 240(C), pages 778-792.
    8. Fei Liu & Ting Nan & Xinliang Wang, 2022. "Causes and Evolution Characteristics of Green Innovation Efficiency Loss: The Perspective of Factor Mismatch under Local Government Competition," Sustainability, MDPI, vol. 14(14), pages 1-29, July.
    9. Dechun Liu & Xinye Zheng & Yihua Yu, 2022. "Public Debt Competition in Local China: Evidence and Mechanism of Spatial Interactions," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 91-105, November.
    10. Yang, Di & Luan, Weixin & Qiao, Lu & Pratama, Mahardhika, 2020. "Modeling and spatio-temporal analysis of city-level carbon emissions based on nighttime light satellite imagery," Applied Energy, Elsevier, vol. 268(C).
    11. Xinye Zheng & Feng Song & Yihua Yu & Shunfeng Song, 2015. "In Search of Fiscal Interactions: A Spatial Analysis of Chinese Provincial Infrastructure Spending," Review of Development Economics, Wiley Blackwell, vol. 19(4), pages 860-876, November.
    12. Wang, Jian & Wu, Qun & Yan, Siqi & Guo, Guancheng & Peng, Shangui, 2020. "China’s local governments breaking the land use planning quota: A strategic interaction perspective," Land Use Policy, Elsevier, vol. 92(C).
    13. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    14. Shi, Kaifang & Yu, Bailang & Huang, Chang & Wu, Jianping & Sun, Xiufeng, 2018. "Exploring spatiotemporal patterns of electric power consumption in countries along the Belt and Road," Energy, Elsevier, vol. 150(C), pages 847-859.
    15. Eleonora Dávalos & Leonardo Fabio Morales, 2019. "Is there a balloon effect? Coca crops and forced eradication in Colombia," Documentos de Trabajo de Valor Público 17350, Universidad EAFIT.
    16. Yajing Liu & Shuai Zhou & Ge Zhang, 2023. "Spatio-Temporal Dynamics and Driving Forces of Multi-Scale Emissions Based on Nighttime Light Data: A Case Study of the Pearl River Delta Urban Agglomeration," Sustainability, MDPI, vol. 15(10), pages 1-24, May.
    17. Yu Xiang & Jing Zheng & Xunhua Tu, 2022. "The Impact of Intermediate Goods Imports on Energy Efficiency: Empirical Evidence from Chinese Cities," IJERPH, MDPI, vol. 19(20), pages 1-23, October.
    18. Zhang, Jianhua & Ballas, Dimitris & Liu, Xiaolong, 2023. "Neighbourhood-level spatial determinants of residential solar photovoltaic adoption in the Netherlands," Renewable Energy, Elsevier, vol. 206(C), pages 1239-1248.
    19. Wanchun Leng & Guojin He & Wei Jiang, 2019. "Investigating the Spatiotemporal Variability and Driving Factors of Artificial Lighting in the Beijing-Tianjin-Hebei Region Using Remote Sensing Imagery and Socioeconomic Data," IJERPH, MDPI, vol. 16(11), pages 1-20, June.
    20. Gibson, John & Boe-Gibson, Geua & Stichbury, Glen, 2015. "Urban land expansion in India 1992–2012," Food Policy, Elsevier, vol. 56(C), pages 100-113.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:64:y:2024:i:4:d:10.1007_s10614-023-10515-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.