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Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data

Policymakers pay much attention to effectively increasing frequency of people’s cycling in the context of developing sustainable and green cities. Investigating associations of environmental characteristics and cycling behaviour could offer implications for changing urban infrastructure aiming at en...

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Autores principales: Sun, Yeran, Du, Yunyan, Wang, Yu, Zhuang, Liyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5486330/
https://www.ncbi.nlm.nih.gov/pubmed/28617345
http://dx.doi.org/10.3390/ijerph14060644
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author Sun, Yeran
Du, Yunyan
Wang, Yu
Zhuang, Liyuan
author_facet Sun, Yeran
Du, Yunyan
Wang, Yu
Zhuang, Liyuan
author_sort Sun, Yeran
collection PubMed
description Policymakers pay much attention to effectively increasing frequency of people’s cycling in the context of developing sustainable and green cities. Investigating associations of environmental characteristics and cycling behaviour could offer implications for changing urban infrastructure aiming at encouraging active travel. However, earlier examinations of associations between environmental characteristics and active travel behaviour are limited by low spatial granularity and coverage of traditional data. Crowdsourced geographic information offers an opportunity to determine the fine-grained travel patterns of people. Particularly, Strava Metro data offer a good opportunity for studies of recreational cycling behaviour as they can offer hourly, daily or annual cycling volumes with different purposes (commuting or recreational) in each street across a city. Therefore, in this study, we utilised Strava Metro data for investigating associations between environmental characteristics and recreational cycling behaviour at a large spatial scale (street level). In this study, we took account of population density, employment density, road length, road connectivity, proximity to public transit services, land use mix, proximity to green space, volume of motor vehicles and traffic accidents in an empirical investigation over Glasgow. Empirical results reveal that Strava cyclists are more likely to cycle for recreation on streets with short length, large connectivity or low volume of motor vehicles or on streets surrounded by residential land.
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spelling pubmed-54863302017-06-30 Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data Sun, Yeran Du, Yunyan Wang, Yu Zhuang, Liyuan Int J Environ Res Public Health Article Policymakers pay much attention to effectively increasing frequency of people’s cycling in the context of developing sustainable and green cities. Investigating associations of environmental characteristics and cycling behaviour could offer implications for changing urban infrastructure aiming at encouraging active travel. However, earlier examinations of associations between environmental characteristics and active travel behaviour are limited by low spatial granularity and coverage of traditional data. Crowdsourced geographic information offers an opportunity to determine the fine-grained travel patterns of people. Particularly, Strava Metro data offer a good opportunity for studies of recreational cycling behaviour as they can offer hourly, daily or annual cycling volumes with different purposes (commuting or recreational) in each street across a city. Therefore, in this study, we utilised Strava Metro data for investigating associations between environmental characteristics and recreational cycling behaviour at a large spatial scale (street level). In this study, we took account of population density, employment density, road length, road connectivity, proximity to public transit services, land use mix, proximity to green space, volume of motor vehicles and traffic accidents in an empirical investigation over Glasgow. Empirical results reveal that Strava cyclists are more likely to cycle for recreation on streets with short length, large connectivity or low volume of motor vehicles or on streets surrounded by residential land. MDPI 2017-06-15 2017-06 /pmc/articles/PMC5486330/ /pubmed/28617345 http://dx.doi.org/10.3390/ijerph14060644 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sun, Yeran
Du, Yunyan
Wang, Yu
Zhuang, Liyuan
Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data
title Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data
title_full Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data
title_fullStr Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data
title_full_unstemmed Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data
title_short Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data
title_sort examining associations of environmental characteristics with recreational cycling behaviour by street-level strava data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5486330/
https://www.ncbi.nlm.nih.gov/pubmed/28617345
http://dx.doi.org/10.3390/ijerph14060644
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