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A global assessment of street network sprawl

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  • Barrington-Leigh, Christopher Paul

    (McGill University)

  • Millard-Ball, Adam

Abstract

Disconnected urban street networks, which we call “street-network sprawl,” are strongly associated with increased vehicle travel, energy use and CO_{2} emissions, as shown by previous research in Europe and North America. In this paper, we provide the first systematic and globally commensurable measures of street-network sprawl based on graph-theoretic and geographic concepts. Using data on all 46 million km of mapped streets worldwide, we compute these measures for the entire Earth at the highest possible resolution. We generate a summary scalar measure for street-network sprawl, the Street-Network Disconnectedness index (SNDi), as well as a data-driven multidimensional classification that identifies eight empirical street-network types that span the spectrum of connectivity, from gridiron to dendritic (tree-like) and circuitous networks. Our qualitative validation shows that both the scalar and multidimensional measures are meaningfully comparable within and across countries, and successfully capture varied dimensions of walkability and urban development. We further show that in select high-income countries, our measures explain cross-sectional variation in household transportation decisions, and a one standard-deviation increase in SNDi is associated with an extra 0.25 cars owned per household. We aggregate our measures to the scale of countries, cities, and smaller geographies and describe patterns in street-network sprawl around the world. Latin America, Japan, South Korea, much of Europe and North Africa stand out for their low levels of street-network sprawl, while the highest levels are found in south-east Asia, the United States and the British Isles.

Suggested Citation

  • Barrington-Leigh, Christopher Paul & Millard-Ball, Adam, 2019. "A global assessment of street network sprawl," OSF Preprints 6vp8j, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:6vp8j
    DOI: 10.31219/osf.io/6vp8j
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    References listed on IDEAS

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    1. David J Giacomin & David M Levinson, 2015. "Road network circuity in metropolitan areas," Environment and Planning B, , vol. 42(6), pages 1040-1053, November.
    2. Pavithra Parthasarathi & Hartwig Hochmair & David Levinson, 2015. "Street network structure and household activity spaces," Urban Studies, Urban Studies Journal Limited, vol. 52(6), pages 1090-1112, May.
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    4. 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.
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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.
    2. Boeing, Geoff & Ha, Jaehyun, 2024. "Resilient by design: Simulating street network disruptions across every urban area in the world," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    3. Boeing, Geoff & Ha, Jaehyun, 2024. "Resilient by Design: Simulating Street Network Disruptions across Every Urban Area in the World," SocArXiv tk93y, Center for Open Science.
    4. Adam Millard-Ball & Purva Kapshikar, 2024. "How land use patterns keep driving cheap: Geographic support for transportation taxes," Urban Studies, Urban Studies Journal Limited, vol. 61(7), pages 1345-1370, May.
    5. Shaye Palagi & Amy Javernick-Will, 2020. "Pathways to Livable Relocation Settlements Following Disaster," Sustainability, MDPI, vol. 12(8), pages 1-25, April.
    6. Boeing, Geoff, 2020. "Street Network Models and Indicators for Every Urban Area in the World," SocArXiv f2dqc, Center for Open Science.

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