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Can More Accurate Night-Time Remote Sensing Data Simulate a More Detailed Population Distribution?

Author

Listed:
  • Nannan Gao

    (Shenzhen Institute of Building Research Co., Ltd., Shenzhen 518049, Guangdong, China
    School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, Guangdong, China)

  • Fen Li

    (Shenzhen Institute of Building Research Co., Ltd., Shenzhen 518049, Guangdong, China)

  • Hui Zeng

    (School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, Guangdong, China)

  • Daniël van Bilsen

    (Engineering and Policy Analysis, Faculty of Technology, Policy and Management Delft University of Technology, 2600 GA Delft, The Netherlands)

  • Martin De Jong

    (Rotterdam School of Management & Erasmus School of Law, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands)

Abstract

Aging, shrinking cities, urban agglomerations and other new key terms continue to emerge when describing the large-scale population changes in various cities in mainland China. It is important to simulate the distribution of residential populations at a coarse scale to manage cities as a whole, and at a fine scale for policy making in infrastructure development. This paper analyzes the relationship between the DN (Digital number, value assigned to a pixel in a digital image) value of NPP-VIIRS (the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite) and LuoJia1-01 and the residential populations of urban areas at a district, sub-district, community and court level, to compare the influence of resolution of remote sensing data by taking urban land use to map out auxiliary data in which first-class (R1), second-class (R2) and third-class residential areas (R3) are distinguished by house price. The results show that LuoJia1-01 more accurately analyzes population distributions at a court level for second- and third-class residential areas, which account for over 85% of the total population. The accuracy of the LuoJia1-01 simulation data is higher than that of Landscan and GHS (European Commission Global Human Settlement) population. This can be used as an important tool for refining the simulation of residential population distributions. In the future, higher-resolution night-time light data could be used for research on accurate simulation analysis that scales down large-scale populations.

Suggested Citation

  • Nannan Gao & Fen Li & Hui Zeng & Daniël van Bilsen & Martin De Jong, 2019. "Can More Accurate Night-Time Remote Sensing Data Simulate a More Detailed Population Distribution?," Sustainability, MDPI, vol. 11(16), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4488-:d:259003
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    References listed on IDEAS

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    4. Qingxu Huang & Yang Yang & Yajing Li & Bin Gao, 2016. "A Simulation Study on the Urban Population of China Based on Nighttime Light Data Acquired from DMSP/OLS," Sustainability, MDPI, vol. 8(6), pages 1-13, May.
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    Cited by:

    1. Sebastian Eichhorn, 2020. "Disaggregating Population Data and Evaluating the Accuracy of Modeled High-Resolution Population Distribution—The Case Study of Germany," Sustainability, MDPI, vol. 12(10), pages 1-21, May.

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