In recent literature, “walkability” is evaluated and measured in terms of both infrastructure connectivity and human-scale streetscape features. Such analyses rely on geospatial data about walking and bicycling facilities, which, in many rural communities, is either non-existent or inaccessible. Situated in the larger “open data” movement, OpenStreetMap (OSM) is a crowdsourced, web-based map and repository for geospatial data, including infrastructure features such as roads, trails, sidewalks, building footprints, parks, and more. We assert that OSM is a powerful source of information that can be used to understand and to model the built environment, especially in rural areas where official spatial data is lacking. In addition to infrastructure geometry, the OSM platform supports the storage of attribute data through the use of tags. We operationalize the idea that OSM can be used as a viable data source for evaluating walkability at the community scale. Using Perry, IA, as a case study, we have employed multiple measures of walkability using both OSM pedestrian data and Iowa Department of Transportation street data for comparison. We found that the inclusion of OSM pedestrian data in walkability analyses greatly improved the results for some measures. Further research will focus on ways to incorporate OSM tags and OSM-sourced community assets and barriers into walkability analysis.
Autor / Author: | Dunn, Austin; Hanson, Bailey; Seeger, Christopher J. |
Institution / Institution: | Iowa State University, Iowa, USA; Iowa State University, Iowa, USA; Iowa State University, Iowa, USA |
Seitenzahl / Pages: | 10 |
Sprache / Language: | Englisch |
Veröffentlichung / Publication: | JoDLA − Journal of Digital Landscape Architecture, 3-2018 |
Tagung / Conference: | Digital Landscape Architecture 2018 – Expanding the Boundaries: Landscape Architecture in a Big Data World |
Veranstaltungsort, -datum / Venue, Date: | Munich-Freising, Germany 30-05-18 - 02-06-18 |
Schlüsselwörter (de): | |
Keywords (en): | Walkability, open data, transportation, pedestrian, design |
Paper review type: | Full Paper Review |
DOI: | doi:10.14627/537642013 |
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