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Measuring the size and growth of cities using nighttime light

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  • Ch, R.
  • Martin, D.
  • Vargas, J.

Abstract

This paper uses high-resolution images of nighttime luminosity to estimate a globally comparable measure of the size of metropolitan areas around the world for the years 2000 and 2010. We apply recently-proposed methodologies that correct the known problems of available nighttime luminosity data including blurring, instability of lit pixels overtime and the reduced comparability of night light images across satellites and across time. We then develop a protocol that isolates stable nighttime light pixels that constitute urban footprint, including low luminosity urban settlements such as slums, and excluding confounding phenomena such as highway illumination. When analyzed together with existing geo-referenced population datasets, our measure of urban footprint, can be used to compute city densities for the entire world. After characterizing some basic stylized facts regarding the distribution of urban sprawl, urban population and population density across world regions, we offer an application of our measure to the study of the size distribution of cities, including test of the Zipf's Law and Gibrat's Law.

Suggested Citation

  • Ch, R. & Martin, D. & Vargas, J., 2018. "Measuring the size and growth of cities using nighttime light," Research Department working papers 1279, CAF Development Bank Of Latinamerica.
  • Handle: RePEc:dbl:dblwop:1279
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    Cited by:

    1. Pierre-Philippe Combes & Clément Gorin & Shohei Nakamura & Mark Roberts & Benjamin Stewart, 2023. "An Anatomy of Urbanization in Sub-Saharan Africa," SciencePo Working papers hal-04345529, HAL.
    2. Chunfang Chai & Yuanrong He & Peng Yu & Yuanmao Zheng & Zhicheng Chen & Menglin Fan & Yongpeng Lin, 2022. "Spatiotemporal Evolution Characteristics of Urbanization in the Xiamen Special Economic Zone Based on Nighttime-Light Data from 1992 to 2020," Land, MDPI, vol. 11(8), pages 1-22, August.
    3. Yifu Ou & Euijune Kim & Xingjian Liu & Kyung-Min Nam, 2023. "Delineating functional regions from road networks: The case of South Korea," Environment and Planning B, , vol. 50(6), pages 1677-1694, July.
    4. Zhongwu Zhang & Yuanfang Liu, 2022. "Spatial Expansion and Correlation of Urban Agglomeration in the Yellow River Basin Based on Multi-Source Nighttime Light Data," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    5. García-Suaza, Andres & Varela, Daniela, 2024. "Nightlight, landcover and buildings: understanding intracity socioeconomic differences," Documentos de Trabajo 21025, Universidad del Rosario.
    6. Xu, Jiajun & Wang, Jinchao & Li, Rui & Yang, Xiaojun, 2023. "Spatio-temporal effects of urbanization on CO2 emissions: Evidences from 268 Chinese cities," Energy Policy, Elsevier, vol. 177(C).
    7. Tanner Regan & Giorgio Chiovelli & Stelios Michalopoulos & Elias Papaioannou, 2023. "Illuminating Africa?," Working Papers 2023-11, The George Washington University, Institute for International Economic Policy.
    8. Omoniyi Alimi & Geua Boe-Gibson & John Gibson, 2022. "Noisy Night Lights Data: Effects on Research Findings for Developing Countries," Working Papers in Economics 22/12, University of Waikato.

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    More about this item

    Keywords

    Ciudades; Desarrollo; Desarrollo urbano; Economía; Políticas públicas;
    All these keywords.

    JEL classification:

    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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