IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v7y2015i10p13469-13499d56624.html
   My bibliography  Save this article

Multi-Scale Measurement of Regional Inequality in Mainland China during 2005–2010 Using DMSP/OLS Night Light Imagery and Population Density Grid Data

Author

Listed:
  • Huimin Xu

    (School of Economics, Zhongnan University of Economics and Law, Wuhan 430073, China)

  • Hutao Yang

    (School of Economics, Zhongnan University of Economics and Law, Wuhan 430073, China)

  • Xi Li

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    Collaborative Innovation Centre of Geospatial Technology, Wuhan 430079, China
    Department of Geographical Sciences, University of Maryland, College Park, 20742 MD, USA)

  • Huiran Jin

    (Department of Geographical Sciences, University of Maryland, College Park, 20742 MD, USA)

  • Deren Li

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    Collaborative Innovation Centre of Geospatial Technology, Wuhan 430079, China)

Abstract

This study used the Night Light Development Index (NLDI) to measure the regional inequality of public services in Mainland China at multiple scales. The NLDI was extracted based on a Gini Coefficient approach to measure the spatial differences of population distribution and night light distribution. Population data were derived from the dataset of China’s population density grid, and night light data were acquired from satellite imagery. In the multi-scale analysis, we calculated the NLDI for China as a whole, eight economic regions, 31 provincial regions, and 354 prefectural cities for the two years of 2005 and 2010. The results indicate that Southwest China and Northwest China are the regions with the most unequal public services, with NLDI values of 0.7116 and 0.7251 for 2005, respectively, and 0.6678 and 0.6304 for 2010, respectively. In contrast, Northern Coastal China had the lowest NLDI values of 0.4775 and 0.4312 for 2005 and 2010, respectively, indicating that this region had the most equal public services. Also, the regional inequality of Mainland China in terms of NLDI has been reduced from 0.6161 to 0.5743 during 2005–2010. The same pattern was observed from the provincial and prefectural analysis, suggesting that public services in Mainland China became more equal within the five-year period. A regression analysis indicated that provincial and prefectural regions with more public services per capita and higher population density had more equal public services.

Suggested Citation

  • Huimin Xu & Hutao Yang & Xi Li & Huiran Jin & Deren Li, 2015. "Multi-Scale Measurement of Regional Inequality in Mainland China during 2005–2010 Using DMSP/OLS Night Light Imagery and Population Density Grid Data," Sustainability, MDPI, vol. 7(10), pages 1-31, September.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:10:p:13469-13499:d:56624
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/7/10/13469/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/7/10/13469/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yingru Li & Yehua Dennis Wei, 2014. "Multidimensional Inequalities in Health Care Distribution in Provincial China: A Case Study of Henan Province," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 105(1), pages 91-106, February.
    2. Zhang, Xiaobo & Kanbur, Ravi, 2005. "Spatial inequality in education and health care in China," China Economic Review, Elsevier, vol. 16(2), pages 189-204.
    3. Ravi Kanbur & Xiaobo Zhang, 2005. "Fifty Years of Regional Inequality in China: a Journey Through Central Planning, Reform, and Openness," Review of Development Economics, Wiley Blackwell, vol. 9(1), pages 87-106, February.
    4. Minghong Tan, 2015. "Urban Growth and Rural Transition in China Based on DMSP/OLS Nighttime Light Data," Sustainability, MDPI, vol. 7(7), pages 1-14, July.
    5. Liu, Tung & Li, Kui-Wai, 2006. "Disparity in factor contributions between coastal and inner provinces in post-reform China," China Economic Review, Elsevier, vol. 17(4), pages 449-470.
    6. Z Zhang & S Yao, 2001. "Regional Inequalities in Contemporary China Measured by GDP and Consumption," Economic Issues Journal Articles, Economic Issues, vol. 6(2), pages 13-30, September.
    7. Wenze Yue & Yuntang Zhang & Xinyue Ye & Yeqing Cheng & Mark R. Leipnik, 2014. "Dynamics of Multi-Scale Intra-Provincial Regional Inequality in Zhejiang, China," Sustainability, MDPI, vol. 6(9), pages 1-22, August.
    8. 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.
    9. Doll, Christopher N.H. & Muller, Jan-Peter & Morley, Jeremy G., 2006. "Mapping regional economic activity from night-time light satellite imagery," Ecological Economics, Elsevier, vol. 57(1), pages 75-92, April.
    10. Guanghua Wan, 2007. "Understanding Regional Poverty And Inequality Trends In China: Methodological Issues And Empirical Findings," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 53(1), pages 25-34, March.
    11. Li, Chao & Gibson, John, 2013. "Rising Regional Inequality in China: Fact or Artifact?," World Development, Elsevier, vol. 47(C), pages 16-29.
    12. Keola, Souknilanh & Andersson, Magnus & Hall, Ola, 2015. "Monitoring Economic Development from Space: Using Nighttime Light and Land Cover Data to Measure Economic Growth," World Development, Elsevier, vol. 66(C), pages 322-334.
    13. Danlin Yu & Yehua Dennis Wei, 2008. "Spatial data analysis of regional development in Greater Beijing, China, in a GIS environment," Papers in Regional Science, Wiley Blackwell, vol. 87(1), pages 97-117, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Feng Lan & Huili Da & Haizhen Wen & Ying Wang, 2019. "Spatial Structure Evolution of Urban Agglomerations and Its Driving Factors in Mainland China: From the Monocentric to the Polycentric Dimension," Sustainability, MDPI, vol. 11(3), pages 1-20, January.
    2. Tingting Xu & Yunting Zong & Heng Su & Aohua Tian & Jay Gao & Yurui Wang & Ruiqi Su, 2023. "Prediction of Multi-Scale Socioeconomic Parameters from Long-Term Nighttime Lights Satellite Data Using Decision Tree Regression: A Case Study of Chongqing, China," Land, MDPI, vol. 12(1), pages 1-22, January.
    3. Huimin Xu & Shougeng Hu & Xi Li, 2023. "Urban Distribution and Evolution of the Yangtze River Economic Belt from the Perspectives of Urban Area and Night-Time Light," Land, MDPI, vol. 12(2), pages 1-21, January.

    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. Rui Hao & Zheng Wei, 2010. "Fundamental causes of inland–coastal income inequality in post-reform China," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(1), pages 181-206, August.
    2. repec:rre:publsh:v:38:y:2008:i:3:p:319-41 is not listed on IDEAS
    3. Corral, Leonardo R. & Schling, Maja, 2017. "The impact of shoreline stabilization on economic growth in small island developing states," Journal of Environmental Economics and Management, Elsevier, vol. 86(C), pages 210-228.
    4. Jing Li & Tsun Se Cheong & Jianfa Shen & Dahai Fu, 2019. "Urbanization And Rural–Urban Consumption Disparity: Evidence From China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(04), pages 983-996, September.
    5. Yuwan Duan & Erik Dietzenbacher & Bart Los & Ruochen Dai, 2023. "Regional inequality in China during its rise as a giant exporter: A value chain analysis," Journal of Regional Science, Wiley Blackwell, vol. 63(1), pages 148-172, January.
    6. Nicolene Hamman & Andrew Phiri, 2022. "Using Nighttime Luminosity as a Proxy for Economic Growth in Africa: Is It a Bright Idea?," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 20(2 (Summer), pages 139-165.
    7. Xing, Li & Fan, Shenggen & Luo, Xiaopeng & Zhang, Xiaobo, 2006. "Village Inequality in Western China," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25390, International Association of Agricultural Economists.
    8. Xiaosu Ye & Lie Ma & Kunhui Ye & Jiantao Chen & Qiu Xie, 2017. "Analysis of Regional Inequality from Sectoral Structure, Spatial Policy and Economic Development: A Case Study of Chongqing, China," Sustainability, MDPI, vol. 9(4), pages 1-17, April.
    9. Felbermayr, Gabriel & Gröschl, Jasmin & Sanders, Mark & Schippers, Vincent & Steinwachs, Thomas, 2018. "Shedding Light on the Spatial Diffusion of Disasters," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181556, Verein für Socialpolitik / German Economic Association.
    10. repec:hal:wpspec:info:hdl:2441/6741 is not listed on IDEAS
    11. Peng Bin & Andrea Fracasso, 2017. "Regional Consumption Inequality in China: An Oaxaca-Blinder Decomposition at the Prefectural Level," Growth and Change, Wiley Blackwell, vol. 48(3), pages 459-486, September.
    12. John Knight, 2014. "Inequality in China: An Overview," The World Bank Research Observer, World Bank, vol. 29(1), pages 1-19.
    13. Celine Bonnefond, 2014. "Growth Dynamics And Conditional Convergence Among Chinese Provinces: A Panel Data Investigation Using System Gmm Estimator," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 39(4), pages 1-25, December.
    14. Hrushikesh Mallick & Mantu Kumar Mahalik & Hemachandra Padhan, 2020. "Does globalization exacerbate income inequality in two largest emerging economies? The role of FDI and remittances inflows," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 67(4), pages 443-480, December.
    15. John Gibson & Chao Li, 2017. "The Erroneous Use Of China'S Population And Per Capita Data: A Structured Review And Critical Test," Journal of Economic Surveys, Wiley Blackwell, vol. 31(4), pages 905-922, September.
    16. repec:hal:spmain:info:hdl:2441/6741 is not listed on IDEAS
    17. Phoebe W. Ishak & Pierre-Guillaume Méon, 2020. "A resource-rich neighbor is a misfortune: The spatial distribution of the resource curse in Brazil," Working Papers CEB 20-001, ULB -- Universite Libre de Bruxelles.
    18. Horridge, Mark & Wittwer, Glyn, 2008. "SinoTERM, a multi-regional CGE model of China," China Economic Review, Elsevier, vol. 19(4), pages 628-634, December.
    19. Jasiński, Tomasz, 2019. "Modeling electricity consumption using nighttime light images and artificial neural networks," Energy, Elsevier, vol. 179(C), pages 831-842.
    20. Qian Chen & Tingting Ye & Naizhuo Zhao & Mingjun Ding & Zutao Ouyang & Peng Jia & Wenze Yue & Xuchao Yang, 2021. "Mapping China’s regional economic activity by integrating points-of-interest and remote sensing data with random forest," Environment and Planning B, , vol. 48(7), pages 1876-1894, September.
    21. Li, Tingting & Lai, Jennifer T. & Wang, Yong & Zhao, Dingtao, 2016. "Long-run relationship between inequality and growth in post-reform China: New evidence from dynamic panel model," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 238-252.
    22. Lu Ming & Zhao Chen & Yongqin Wang & Yan Zhang & Yuan Zhang & Changyuan Luo, 2013. "China’s Economic Development," Books, Edward Elgar Publishing, number 14502.
    23. Juan Jose Miranda & Oscar A. Ishizawa & Hongrui Zhang, 2020. "Understanding the Impact Dynamics of Windstorms on Short-Term Economic Activity from Night Lights in Central America," Economics of Disasters and Climate Change, Springer, vol. 4(3), pages 657-698, October.

    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:gam:jsusta:v:7:y:2015:i:10:p:13469-13499:d:56624. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.