Visualising where commuting cyclists travel using crowdsourced data

McArthur, D. P. and Hong, J. (2019) Visualising where commuting cyclists travel using crowdsourced data. Journal of Transport Geography, 74, pp. 233-241. (doi: 10.1016/j.jtrangeo.2018.11.018)

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Encouraging more cycling is increasingly seen as an important way to create more sustainable cities and to improve public health. Understanding how cyclists travel and how to encourage cycling requires data; something which has traditionally been lacking. New sources of data are emerging which promise to reveal new insights. In this paper, we use data from the activity tracking app Strava to examine where people in Glasgow cycle and how new forms of data could be utilised to better understand cycling patterns. We propose a method for augmenting the data by comparing the observed link flows to the link flows which would have resulted if people took the shortest route. Comparing these flows gives some expected results, for example, that people like to cycle along the river, as well as some unexpected results, for example, that some routes with cycling infrastructure are avoided by cyclists. This study proposes a practical approach that planners can use for cycling plans with new/emerging cycling data.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Hong, Dr Jinhyun and Mcarthur, Dr David
Authors: McArthur, D. P., and Hong, J.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Journal of Transport Geography
ISSN (Online):1873-1236
Published Online:06 December 2018
Copyright Holders:Copyright © 2018 The Authors
First Published:First published in Journal of Transport Geography 74: 233-241
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
651921Urban Big Data Research CentrePiyushimita ThakuriahEconomic and Social Research Council (ESRC)ES/L011921/1SPS - URBAN STUDIES