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Street Network Models and Indicators for Every Urban Area in the World

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  • Boeing, Geoff

    (Northeastern University)

Abstract

Cities worldwide exhibit a variety of street network patterns and configurations that shape human mobility, equity, health, and livelihoods. This study models and analyzes the street networks of every urban area in the world, using boundaries derived from the Global Human Settlement Layer. Street network data are acquired and modeled from OpenStreetMap with the open‐source OSMnx software. In total, this study models over 160 million OpenStreetMap street network nodes and over 320 million edges across 8,914 urban areas in 178 countries, and attaches elevation and grade data. This article presents the study’s reproducible computational workflow, introduces two new open data repositories of ready‐to‐use global street network models and calculated indicators, and discusses summary findings on street network form worldwide. It makes four contributions. First, it reports the methodological advances of this open‐source workflow. Second, it produces an open data repository containing street network models for each urban area. Third, it analyzes these models to produce an open data repository containing street network form indicators for each urban area. No such global urban street network indicator data set has previously existed. Fourth, it presents a summary analysis of urban street network form, reporting the first such worldwide results in the literature.

Suggested Citation

  • Boeing, Geoff, 2021. "Street Network Models and Indicators for Every Urban Area in the World," SocArXiv f2dqc_v1, Center for Open Science.
  • Handle: RePEc:osf:socarx:f2dqc_v1
    DOI: 10.31219/osf.io/f2dqc_v1
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    References listed on IDEAS

    as
    1. Stephen Marshall & Jorge Gil & Karl Kropf & Martin Tomko & Lucas Figueiredo, 2018. "Street Network Studies: from Networks to Models and their Representations," Networks and Spatial Economics, Springer, vol. 18(3), pages 735-749, September.
    2. Barrington-Leigh, Christopher Paul & Millard-Ball, Adam, 2019. "A global assessment of street network sprawl," OSF Preprints 6vp8j, Center for Open Science.
    3. Boeing, Geoff, 2020. "The Right Tools for the Job: The Case for Spatial Science Tool-Building," SocArXiv d267g, Center for Open Science.
    4. M. T. Gastner & M. E.J. Newman, 2006. "The spatial structure of networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 49(2), pages 247-252, January.
    5. Alessandro Vespignani, 2018. "Twenty years of network science," Nature, Nature, vol. 558(7711), pages 528-529, June.
    6. A. P. Masucci & D. Smith & A. Crooks & M. Batty, 2009. "Random planar graphs and the London street network," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 259-271, September.
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    Cited by:

    1. Liu, Shiqin & Higgs, Carl & Arundel, Jonathan & Boeing, Geoff & Cerdera, Nicholas & Moctezuma, David & Cerin, Ester & Adlakha, Deepti & Lowe, Melanie & Giles-Corti, Billie, 2021. "A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data," SocArXiv cua35_v1, Center for Open Science.

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