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

Listed author(s):
  • 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)

Registered author(s):

    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.

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    Article provided by MDPI, Open Access Journal in its journal Sustainability.

    Volume (Year): 7 (2015)
    Issue (Month): 10 (September)
    Pages: 1-31

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    Handle: RePEc:gam:jsusta:v:7:y:2015:i:10:p:13469-13499:d:56624
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    1. Zhang, Xiaobo & Kanbur, Ravi, 2005. "Spatial inequality in education and health care in China," China Economic Review, Elsevier, vol. 16(2), pages 189-204.
    2. 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.
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    4. 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, Open Access Journal, vol. 6(9), pages 1-22, August.
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    6. 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.
    7. 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, 03.
    8. Li, Chao & Gibson, John, 2013. "Rising Regional Inequality in China: Fact or Artifact?," World Development, Elsevier, vol. 47(C), pages 16-29.
    9. 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.
    10. 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, 03.
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