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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

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, Open Access Journal, vol. 7(10), pages 1-31, September.
  • Handle: RePEc:gam:jsusta:v:7:y:2015:i:10:p:13469-13499:d:56624
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    References listed on IDEAS

    as
    1. Li, Chao & Gibson, John, 2013. "Rising Regional Inequality in China: Fact or Artifact?," World Development, Elsevier, vol. 47(C), pages 16-29.
    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. 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, Open Access Journal, vol. 6(11), pages 1-16, November.
    4. 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.
    5. 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.
    6. 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.
    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, Open Access Journal, vol. 6(9), pages 1-22, August.
    8. 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.
    9. 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.
    10. 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.
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    More about this item

    Keywords

    regional inequality; China; Lorenz Curve; night light; remote sensing;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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