IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/hmhts_v1.html
   My bibliography  Save this paper

A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood

Author

Listed:
  • Boeing, Geoff

    (Northeastern University)

Abstract

OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks from OpenStreetMap at metropolitan, municipal, and neighborhood scales - namely, every US city and town, census urbanized area, and Zillow-defined neighborhood. It presents empirical findings on US urban form and street network characteristics, emphasizing measures relevant to graph theory, transportation, urban design, and morphology such as structure, connectedness, density, centrality, and resilience. In the past, street network data acquisition and processing have been challenging and ad hoc. This study illustrates the use of OSMnx and OpenStreetMap to consistently conduct street network analysis with extremely large sample sizes, with clearly defined network definitions and extents for reproducibility, and using nonplanar, directed graphs. These street networks and measures data have been shared in a public repository for other researchers to use.

Suggested Citation

  • Boeing, Geoff, 2018. "A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood," SocArXiv hmhts_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:hmhts_v1
    DOI: 10.31219/osf.io/hmhts_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/58dc18c0594d9001f79750a9/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/hmhts_v1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Wei-Chien-Benny Chin & Tzai-Hung Wen, 2015. "Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-23, October.
    2. Geoff Boeing, 2020. "Planarity and street network representation in urban form analysis," Environment and Planning B, , vol. 47(5), pages 855-869, June.
    3. Skyler J. Cranmer & Philip Leifeld & Scott D. McClurg & Meredith Rolfe, 2017. "Navigating the Range of Statistical Tools for Inferential Network Analysis," American Journal of Political Science, John Wiley & Sons, vol. 61(1), pages 237-251, January.
    4. J. Buhl & J. Gautrais & N. Reeves & R. V. Solé & S. Valverde & P. Kuntz & G. Theraulaz, 2006. "Topological patterns in street networks of self-organized urban settlements," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 49(4), pages 513-522, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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, 2019. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood," SocArXiv 7fxjz_v1, Center for Open Science.
    3. 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.
    4. Sohouenou, Philippe Y.R. & Christidis, Panayotis & Christodoulou, Aris & Neves, Luis A.C. & Presti, Davide Lo, 2020. "Using a random road graph model to understand road networks robustness to link failures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
    5. Shiguang Wang & Dexin Yu & Mei-Po Kwan & Huxing Zhou & Yongxing Li & Hongzhi Miao, 2019. "The Evolution and Growth Patterns of the Road Network in a Medium-Sized Developing City: A Historical Investigation of Changchun, China, from 1912 to 2017," Sustainability, MDPI, vol. 11(19), pages 1-25, September.
    6. Jiang, Bin, 2007. "A topological pattern of urban street networks: Universality and peculiarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 647-655.
    7. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    8. Lorenzo Barbieri & Roberto D’Autilia & Paola Marrone & Ilaria Montella, 2023. "Graph Representation of the 15-Minute City: A Comparison between Rome, London, and Paris," Sustainability, MDPI, vol. 15(4), pages 1-14, February.
    9. Mundt, Philipp, 2021. "The formation of input–output architecture: Evidence from the European Union," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 89-104.
    10. Wagner, Roy, 2008. "On the metric, topological and functional structures of urban networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2120-2132.
    11. Jinping Lin & Kangmin Wu, 2023. "Intercity asymmetrical linkages influenced by Spring Festival migration and its multivariate distance determinants: a case study of the Yangtze River Delta Region in China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    12. Elijah Knaap & Sergio Rey, 2024. "Segregated by design? Street network topological structure and the measurement of urban segregation," Environment and Planning B, , vol. 51(7), pages 1408-1429, September.
    13. Heng Ye & Zhiping Li & Guangyue Li & Yiran Liu, 2022. "Topology Analysis of Natural Gas Pipeline Networks Based on Complex Network Theory," Energies, MDPI, vol. 15(11), pages 1-20, May.
    14. Róbert Pethes & Levente Kovács, 2023. "An Exact and an Approximation Method to Compute the Degree Distribution of Inhomogeneous Random Graph Using Poisson Binomial Distribution," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    15. Hao Wu & David Levinson, 2020. "Unifying Access," Working Papers 2022-01, University of Minnesota: Nexus Research Group.
    16. De Nicola, Giacomo & Fritz, Cornelius & Mehrl, Marius & Kauermann, Göran, 2023. "Dependence matters: Statistical models to identify the drivers of tie formation in economic networks," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 351-363.
    17. Boeing, Geoff & Ha, Jaehyun, 2024. "Resilient by Design: Simulating Street Network Disruptions across Every Urban Area in the World," SocArXiv tk93y_v1, Center for Open Science.
    18. Rodríguez-Fuentes, Marian & Zepeda-Domínguez, José Alberto & Kluger, Lotta C. & Fumero-Andreu, Claudia María & Ponce-Díaz, Germán & Zetina-Rejón, Manuel J., 2025. "Supply networks of fisheries social-ecological systems: A systematic review of the network approach," Ecological Economics, Elsevier, vol. 227(C).
    19. Boeing, Geoff, 2017. "Methods and Measures for Analyzing Complex Street Networks and Urban Form," SocArXiv 93h82_v1, Center for Open Science.
    20. Zhang, Qiang & Du, Debin & Xia, Qifan & Ding, Junfeng, 2024. "Revealing the energy pyramid: Global energy dependence network and national status based on industry chain," Applied Energy, Elsevier, vol. 367(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:socarx:hmhts_v1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://arabixiv.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.