Using crowdsourced data to monitor change in spatial patterns of bicycle ridership

Publication date: Available online 21 March 2018 Source:Journal of Transport & Health Author(s): Darren Boss, Trisalyn Nelson, Meghan Winters, Colin J. Ferster Cycling is a sustainable mode of transportation with numerous health, environmental and social benefits. Investments in cycling specific infrastructure are being made with the goal of increasing ridership and population health benefits. New infrastructure has the potential to impact the upgraded corridor as well as nearby street segments and cycling patterns across the city. Evaluation of the impact of new infrastructure is often limited to manual or automated counts of cyclists before and after construction, or to aggregate statistics for a large region. Due to methodological limitations and a lack of data, few spatially explicit approaches have been applied to evaluate how patterns of ridership change following investment in cycling infrastructure. Our goal is to demonstrate spatial analysis methods that can be applied to emerging sources of crowdsourced cycling data to monitor changes in the spatial-temporal distribution of cyclists across a city. Specifically, we use crowdsourced ridership data from Strava to examine changes in the spatial-temporal distribution of cyclists in Ottawa-Gatineau, Canada, using local indicators of spatial autocorrelation. Strava samples of bicyclists were correlated with automated counts at 11 locations and correlations ranged for 0.76 to 0.96. Using a local indicator of s...
Source: Journal of Transport and Health - Category: Occupational Health Source Type: research