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

Geoff Boeing

No f2dqc, SocArXiv from Center for Open Science

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.

Date: 2020-09-18
New Economics Papers: this item is included in nep-big and nep-ure
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:f2dqc

DOI: 10.31219/osf.io/f2dqc

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