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Identification of Shrinkage and Growth Patterns of a Shrinking City in China Based on Nighttime Light Data: A Case Study of Yichun

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  • Ying Zhou

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

  • Chenggu Li

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

  • Zuopeng Ma

    (Northeast Institute of Geography and Agroecology, Chines Academy of Science, Changchun 130102, China)

  • Shuju Hu

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

  • Jing Zhang

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

  • Wei Liu

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

Abstract

Urban shrinkage has become a topic of major concern to scholars of geography and urban science. However, the methods of identifying urban shrinkage and growth have mostly focused on traditional statistical methods, and studies based on nighttime light (NTL) data are rare. Here, we use the NTL data for 56 months from 2012 to 2019 obtained by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar Orbiting Partnership (NPP) to identify the shrinkage and growth patterns of Yichun in China, by calculating the slope of the NTL radiance value after denoising. At the same time, by combining high-resolution Google satellite images and traditional demographic data, we analyzed the shrinkage characteristics of Yichun. The results of the study confirmed the characteristics of partial shrinkage in China’s shrinking cities. In addition, the use of NPP-VIIRS NTL data was able to more accurately identify the urban shrinkage and growth patterns, and may also be seen to present a more objective picture of reality, thus providing a new perspective for studies of urban shrinkage.

Suggested Citation

  • Ying Zhou & Chenggu Li & Zuopeng Ma & Shuju Hu & Jing Zhang & Wei Liu, 2019. "Identification of Shrinkage and Growth Patterns of a Shrinking City in China Based on Nighttime Light Data: A Case Study of Yichun," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:6906-:d:294217
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    References listed on IDEAS

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    1. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    2. 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.
    3. Thorsten Wiechmann & Karina M. Pallagst, 2012. "Urban shrinkage in Germany and the USA: A Comparison of Transformation Patterns and Local Strategies," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 36(2), pages 261-280, March.
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    Cited by:

    1. Wei Gao & Xinzheng Zhao & Jianwei Li & Dekang Zhang & Yang Rui & Tongsheng Li & Min Lei, 2022. "Spatiotemporal Pattern Identification and Driving Mechanism of Urban Shrinkage in the Yellow River Basin from 2000 to 2020," Land, MDPI, vol. 11(8), pages 1-19, August.
    2. Changqing Sui & Wei Lu, 2021. "Study on the Urban Fringe Based on the Expansion–Shrinking Dynamic Pattern," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    3. Yihao Jiang & Zhaojin Chen & Pingjun Sun, 2022. "Urban Shrinkage and Urban Vitality Correlation Research in the Three Northeastern Provinces of China," IJERPH, MDPI, vol. 19(17), pages 1-22, August.
    4. Zhenxing Jin & Chengxin Wang & Shangkun Yu & Shuai Zhang & Xiaoming Ding, 2022. "Spatiotemporal evolution and influencing factors of urban shrinkage in the Yellow River Basin, China," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-19, March.
    5. Na Jiang & Andrew T Crooks & Hamdi Kavak & Wenjing Wang, 2024. "Leveraging newspapers to understand urban issues: A longitudinal analysis of urban shrinkage in Detroit," Environment and Planning B, , vol. 51(5), pages 1089-1103, June.

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