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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 each urban area in the world, using boundaries derived from the Global Human Settlement Layer. Street network data are acquired and modeled using the open-source OSMnx software and OpenStreetMap. In total, this study models over 150 million OpenStreetMap street network nodes and over 300 million edges across 9,000 urban areas in 178 countries. This paper presents the study's reproducible computational workflow, introduces two new open data repositories of processed global street network models and calculated indicators, and reports summary descriptive findings on street network form worldwide. It makes four contributions. First, it reports the methodological advances of using this open-source tool in spatial network modeling and analyses with open big data. Second, it produces an open data repository containing street network models for each of these urban areas, in various file formats, for public reuse. Third, it analyzes these models to produce an open data repository containing dozens of street network form indicators for each urban area. No such global urban street network indicator data set has previously existed. Fourth, it presents an aggregate summary descriptive analysis of global street network form at the scale of the urban area, reporting the first such worldwide results in the literature.

Suggested Citation

  • Boeing, Geoff, 2020. "Street Network Models and Indicators for Every Urban Area in the World," SocArXiv f2dqc, Center for Open Science.
  • Handle: RePEc:osf:socarx:f2dqc
    DOI: 10.31219/osf.io/f2dqc
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    References listed on IDEAS

    as
    1. Geoff Boeing, 2020. "A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood," Environment and Planning B, , vol. 47(4), pages 590-608, May.
    2. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, 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. Alessandro Vespignani, 2018. "Twenty years of network science," Nature, Nature, vol. 558(7711), pages 528-529, June.
    5. da Cruz, Nuno F. & Oh, Do Young & Badaoui Choumar, Nathalie, 2020. "The metropolitan scale," LSE Research Online Documents on Economics 103316, London School of Economics and Political Science, LSE Library.
    6. 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.
    7. Boeing, Geoff, 2019. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood," SocArXiv 7fxjz, Center for Open Science.
    8. 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.
    9. Manfred M. Fischer & Peter Nijkamp (ed.), 2014. "Handbook of Regional Science," Springer Books, Springer, edition 127, number 978-3-642-23430-9, July.
    10. Boeing, Geoff, 2018. "Urban Spatial Order: Street Network Orientation, Configuration, and Entropy," SocArXiv qj3p5, Center for Open Science.
    11. 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.
    12. Barrington-Leigh, Christopher Paul & Millard-Ball, Adam, 2019. "A global assessment of street network sprawl," OSF Preprints 6vp8j, Center for Open Science.
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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, Center for Open Science.

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