Authors: Jaimy Fischer*, Simon Fraser University, Trisalyn Nelson, University of California, Santa Barbara, Jeneva Beairsto, Simon Fraser University, Meghan Winters, Simon Fraser University
Topics: Transportation Geography, Temporal GIS, Spatial Analysis & Modeling
Keywords: COVID-19, active transportation, bicycling, Strava
Session Type: Virtual Paper
Start / End Time: 9:35 AM / 10:50 AM
Room: Virtual 33
Presentation File: No File Uploaded
The COVID-19 pandemic has prompted a shift toward active travel for mobility and physical activity. However, changes in mobility patterns in Canada are difficult to quantify due to a lack of real-time travel data. Crowdsourced mobility data may offer insights. For example, Strava, a popular mobile fitness app, collects spatially and temporally continuous mobility data (Strava Metro) which has increasingly been used in bicycling research. Caveats about representativeness and sample bias related to the demographics of app users are important when using Strava data. Even so, Strava data may be an acceptable proxy for ridership patterns when considered alongside official bicycle counts. Our goal is twofold: to estimate whether there were significant changes in bicycling patterns in spring-summer of 2020, and to evaluate the utility of Strava for monitoring bicycling activity through the COVID-19 pandemic. Using Strava and official count data for 2019 and 2020, we examine changes in the spatial-temporal distribution of bicycling activities in Vancouver and Victoria, BC—cities with neighborhoods situated at different places on the urban-rural spectrum and with varied levels of bicycle infrastructure investment. We mapped differences in normalized ridership and applied a local indicator of spatial autocorrelation to quantify patterns of changes in overall and peak/off-peak ridership. Findings are contextualized by comparing trends with key COVID-19 public health intervention policies. Our analysis offers insights on how Strava can be used for monitoring COVID-19’s impact on active transportation, with considerations for how the data might be used in places without official count data.