Exploiting crowdsourced geographic information and GIS for assessment of air pollution exposure during active travel
Sun, Yeran and Moshfeghi, Yashar and Liu, Zhang (2017) Exploiting crowdsourced geographic information and GIS for assessment of air pollution exposure during active travel. Journal of Transport & Health, 6. pp. 93-104. ISSN 2214-1405 (https://doi.org/10.1016/j.jth.2017.06.004)
Preview |
Text.
Filename: Sun_etal_JTH_2017_Exploiting_crowdsourced_geographic_information.pdf
Final Published Version License: Download (1MB)| Preview |
Abstract
Improvement on assessment of air pollution exposure will enhance assessment of health risk-benefit when active travel (cycling and walking). Earlier studies assessed air pollution exposure according to travel time and city-level air pollution. The lack of spatially fine-grained travel data is a barrier to an accurate assessment of air pollution exposure. Due to a high-level spatial granularity, Strava Metro provides an opportunity to assessing air pollution exposure in combination with spatially varying air pollution concentrations. Strava Metro anonymized and aggregated a large volume of users’ traces to streets for each city. In this study, to explore the potential of crowdsourced geographic information in research of active travel and health, we used Strava Metro data and GIS technologies to assess air pollution exposure in Glasgow, UK. Particularly, we incorporated time of the trip to assess average inhaled dose of pollutant during a single cycling or pedestrian trip. Empirical results demonstrate that Strava Metro data provides an opportunity to an assessment of average air pollution exposure during active travel. Additionally, to demonstrate the potential of Strava Metro data in policy-making, we explored the spatial association of air pollution concentration and active travel. As a result, we identified areas that require investment priority, and finally offered implications for policies.
ORCID iDs
Sun, Yeran, Moshfeghi, Yashar ORCID: https://orcid.org/0000-0003-4186-1088 and Liu, Zhang;-
-
Item type: Article ID code: 61897 Dates: DateEvent30 September 2017Published16 June 2017Published Online11 June 2017AcceptedSubjects: Bibliography. Library Science. Information Resources > Library Science. Information Science Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 02 Oct 2017 10:58 Last modified: 11 Nov 2024 11:48 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/61897