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Delineating urban areas using building density

Author

Listed:
  • Marie-Pierre de Bellefon

    (Insee and Paris School of Economics, 48 Boulevard Jourdan, 75014 Paris, France)

  • Pierre-Philippe Combes

    (Univ Lyon, CNRS, GATE UMR 5824, 93 Chemin des Mouilles, 69131 Ecully, France and Sciences Po, Economics Department, 28, Rue des Saints-Pères, 75007 Paris, France; Also affiliated with the Centre for Economic Policy Research and the Institute for the Study of Labor (IZA))

  • Gilles Duranton

    (Wharton School, University of Pennsylvania, 3620 Locust Walk, Philadelphia, pa 19104, USA; Also affiliated with the National Bureau of Economic Research and the Center for Economic Policy Research)

  • Laurent Gobillon

    (PSE-CNRS, 48 Boulevard Jourdan, 75014 Paris, France; Also affiliated with the Centre for Economic Policy Research and the Institute for the Study of Labor (IZA))

  • Clément Gorin

    (Univ Lyon, CNRS, GATE UMR 5824, 93 Chemin des Mouilles, 69131 Ecully, France)

Abstract

We develop a new dartboard methodology to delineate urban areas using detailed information about building location, which we implement using a map of all buildings in France. For each pixel, our approach compares actual building density after smoothing to counterfactual smoothed building density computed after randomly redistributing buildings. We define as urban any area with statistically significant excess building density. Within urban areas, extensions to our approach allow us to distinguish ‘core’ urban pixels and detect centres and subcentres. Finally, we develop novel one- and two-sided tests that provide a statistical basis to compare maps with different delineations, which we use to assess the robustness of our approach and to document large differences between our preferred delineation and the corresponding official one.

Suggested Citation

  • Marie-Pierre de Bellefon & Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon & Clément Gorin, 2019. "Delineating urban areas using building density," Working Papers 1931, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
  • Handle: RePEc:gat:wpaper:1931
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    5. Daniel Arribas-Bel & Miquel-Àngel Garcia-López & Elisabet Viladecans-Marsal, 2019. "Building(s and) cities: delineating urban areas with a machine learning algorithm," Working Papers 2019/10, Institut d'Economia de Barcelona (IEB).

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    More about this item

    Keywords

    urban area definition; dartboard approach; Jaccard indices;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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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