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Safety 2016, 2(3), 17; doi:10.3390/safety2030017

Mapping Bicycle Crash Risk Patterns on the Local Scale

Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria
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Academic Editor: Jake Olivier
Received: 21 March 2016 / Revised: 20 June 2016 / Accepted: 22 August 2016 / Published: 1 September 2016
(This article belongs to the Special Issue The Return of Cycling—Safety Implications)
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Abstract

Currently, mainly aggregated statistics are used for bicycle crash risk calculations. Thus, the understanding of spatial patterns at local scale levels remains vague. Using an agent-based flow model and a bicycle crash database covering 10 continuous years of observation allows us to calculate and map the crash risk on various spatial scales for the city of Salzburg (Austria). In doing so, we directly account for the spatial heterogeneity of crash occurrences. Additionally, we provide a measure for the statistical robustness on the level of single reference units and consider modifiable areal unit problem (MAUP) effects in our analysis. This study is the first of its kind. The results facilitate a better understanding of spatial patterns of bicycle crash rates on the local scale. This is especially important for cities that strive to improve the safety situation for bicyclists in order to address prevailing safety concerns that keep people from using the bicycle as a utilitarian mode of (urban) transport. View Full-Text
Keywords: bicycle; crash; risk; geographical information systems (GIS); spatial analysis; scale; modifiable areal unit problem (MAUP) bicycle; crash; risk; geographical information systems (GIS); spatial analysis; scale; modifiable areal unit problem (MAUP)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Loidl, M.; Wallentin, G.; Wendel, R.; Zagel, B. Mapping Bicycle Crash Risk Patterns on the Local Scale. Safety 2016, 2, 17.

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