• Home
  • About

GIScience News Blog

News of Heidelberg University’s GIScience Research Group.

Feed on
Posts
Comments
« Alexander von Humboldt PostDoc Fellowship for A. Yair Grinberger for Big Spatial Data Research in Heidelberg
The Identification of Geographic Activity Contexts - Invitation to Colloquium Mon 03rd April HD »

Utilizing crowdsourced data for studies of cycling and air pollution

Mar 31st, 2017 by m01

Recently, Strava, a popular website and mobile app dedicated to tracking athletic activity (cycling and running), began offering a data service called Strava Metro, designed to help transportation researchers and urban planners to improve infrastructure for cyclists and pedestrians. Strava Metro data has the potential to promote studies of cycling and health by indicating where commuting and non-commuting cycling activities are at a large spatial scale (street level and intersection level). The assessment of spatially varying effects of air pollution during active travel (cycling or walking) might benefit from Strava Metro data, as a variation in air pollution levels within a city would be expected.

In order to explore the potential of Strava Metro data in research of active travel and health, we investigated spatial patterns of non-commuting cycling activities and associations between cycling purpose (commuting and non-commuting) and air pollution exposure at a large scale. Additionally, we estimated the number of non-commuting cycling trips according to environmental characteristics that may help identify cycling behavior. Researchers who are undertaking studies relating to cycling purpose could benefit from this approach in their use of cycling trip data sets that lack trip purpose. We used the Strava Metro Nodes data from Glasgow, United Kingdom in an empirical study.

Empirical results reveal some findings that (1) when compared with commuting cycling activities, non-commuting cycling activities are more likely to be located in outskirts of the city; (2) spatially speaking, cyclists riding for recreation and other purposes are more likely to be exposed to relatively low levels of air pollution than cyclists riding for commuting; and (3) the method for estimating the number of non-commuting cycling activities works well in this study. The results highlight: (1) a need for policymakers to consider how to improve cycling infrastructure and road safety in outskirts of cities; and (2) a possible way of estimating the number of non-commuting cycling activities when the trip purpose of cycling data is unknown.

Sun, Y., & Mobasheri, A. (2017). Utilizing Crowdsourced Data for Studies of Cycling and Air Pollution Exposure: A Case Study Using Strava Data. International Journal of Environmental Research and Public Health, 14(3), 274.

Tags: air pollution exposure, Crowdsourcing, Cycling, Strava Metro

Posted in Publications, Research, VGI Group

Comments are closed.

  • About

    GIScience News Blog
    News of Heidelberg University’s GIScience Research Group.
    There are 1,480 Posts and 0 Comments so far.

  • Meta

    • Log in
    • Entries RSS
    • Comments RSS
    • WordPress.org
  • Recent Posts

    • Press release: Understanding the Spatial and Temporal Dimensions of Landscape Dynamics
    • Wanna give feedback about HeiGIT services? Survey Deadline extended to 05.03.
    • An ohsome Railway Network Visualization and Analysis
    • Humanitarian OSM Stats: How to monitor humanitarian mapping in the HOT Tasking Manager? - Part 3
    • ISCRAM GIS Track: Deadline extended for WiP and Practitioner papers: February 21, 2021
  • Tags

    3D 3DGEO Big Spatial Data CAP4Access Citizen Science Colloquium crisis mapping Crowdsourcing data quality disaster DisasterMapping GeoNet.MRN GIScience heigit HOT humanitarian Humanitarian OpenStreetMap team intrinsic quality analysis landuse laser scanning Lidar Mapathon MapSwipe Missing Maps MissingMaps ohsome ohsome example Open data openrouteservice OpenStreetMap OSM OSM History Analytics OSMlanduse Quality quality analysis remote sensing routing social media spatial analysis Teaching terrestrial laser scanning Twitter VGI Wheelchair Navigation Workshop
  • Archives

    • March 2021
    • February 2021
    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • March 2020
    • February 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    • December 2016
    • November 2016
    • October 2016
    • September 2016
    • August 2016
    • July 2016
    • June 2016
    • May 2016
    • April 2016
    • March 2016
    • February 2016
    • January 2016
    • December 2015
    • November 2015
    • October 2015
    • September 2015
    • August 2015
    • July 2015
    • June 2015
    • May 2015
    • April 2015
    • March 2015
    • February 2015
    • January 2015
    • December 2014
    • November 2014
    • October 2014
    • September 2014
    • August 2014
    • July 2014
    • June 2014
    • May 2014
    • April 2014
    • March 2014
    • February 2014
    • January 2014
    • December 2013
    • November 2013
    • October 2013
    • September 2013
    • August 2013
    • July 2013
    • June 2013
    • May 2013
    • April 2013
  •  

    March 2017
    M T W T F S S
    « Feb   Apr »
     12345
    6789101112
    13141516171819
    20212223242526
    2728293031  
  • Recent Comments

    GIScience News Blog CC by-nc-sa Some Rights Reserved.

    Free WordPress Themes | Fresh WordPress Themes