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Detecting Urban Markets with Satellite Imagery: An Application to India

Author

Listed:
  • Kathryn Baragwanath Vogel
  • Ran Goldblatt
  • Gordon H. Hanson
  • Amit K. Khandelwal

Abstract

We propose a methodology for defining urban markets based on built-up land-cover classified from daytime satellite imagery. Compared to markets defined using minimum thresholds for nighttime light intensity, daytime imagery identify an order of magnitude more markets, capture more of India's urban population, are more realistically jagged in shape, and reveal more variation in the spatial distribution of economic activity. We conclude that daytime satellite data are a promising source for the study of urban forms.

Suggested Citation

  • Kathryn Baragwanath Vogel & Ran Goldblatt & Gordon H. Hanson & Amit K. Khandelwal, 2018. "Detecting Urban Markets with Satellite Imagery: An Application to India," NBER Working Papers 24796, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24796
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    Cited by:

    1. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    2. Dai, Tianran & Schiff, Nathan, 2023. "The structure and growth of ethnic neighborhoods," Journal of Urban Economics, Elsevier, vol. 137(C).
    3. Gbandi, Tchapo, 2018. "Les Night Lights et QGis : Approximation du gap de revenu urbain-rural [Night Lights Data and QGis: Approximating rural-urban income gap]," MPRA Paper 118347, University Library of Munich, Germany.
    4. Brülhart, Marius & Desmet, Klaus & Klinke, Gian-Paolo, 2020. "The shrinking advantage of market potential," Journal of Development Economics, Elsevier, vol. 147(C).
    5. Chen, Ting & Gu, Yizhen & Zou, Ben, 2024. "China’s commuting-based metropolitan areas," Journal of Urban Economics, Elsevier, vol. 144(C).
    6. Zhang, Bin & Xin, Qingyao & Chen, Siyuan & Yang, Zhiying & Wang, Zhaohua, 2024. "Urban spatial structure and commuting-related carbon emissions in China: Do monocentric cities emit more?," Energy Policy, Elsevier, vol. 186(C).
    7. Julio A. Berdegué & Tatiana Hiller & Juan Mauricio Ramírez & Santiago Satizábal & Isidro Soloaga & Juan Soto & Miguel Uribe & Olga Vargas, 2019. "Delineating functional territories from outer space," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 28(1), pages 1-24, December.
    8. Imryoung Jeong & Hyunjoo Yang, 2021. "Using maps to predict economic activity," Papers 2112.13850, arXiv.org, revised Apr 2022.
    9. Andres García-Suaza & Daniela Varela, 2024. "Nightlight, landcover and buildings: understanding intracity socioeconomic differences," Documentos de Trabajo 21025, Universidad del Rosario.
    10. Lee, Yoonseok & Wang, Yulong, 2023. "Threshold regression with nonparametric sample splitting," Journal of Econometrics, Elsevier, vol. 235(2), pages 816-842.
    11. Dingel, Jonathan I. & Miscio, Antonio & Davis, Donald R., 2021. "Cities, lights, and skills in developing economies," Journal of Urban Economics, Elsevier, vol. 125(C).

    More about this item

    JEL classification:

    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics

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