A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood
Environment and Planning B: Urban Analytics and City Science, DOI: 10.1177/2399808318784595
18 Pages Posted: 3 Apr 2017 Last revised: 6 Aug 2018
Date Written: August 28, 2018
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.
Keywords: network analysis, street network, graph theory, neighborhood, big data, density, python, urban form, land use, networks, GIS, city planning, urban design, geospatial, transportation, OpenStreetMap, OSMnx, resilience, urban morphology, Zillow, centrality, connectivity, betweenness centrality
JEL Classification: C4, D85, N91, N92, O18, P25, R40, R42, R14, R52
Suggested Citation: Suggested Citation