Change detection using Strava Metro

Authors: Colin Ferster*, University of Victoria
Topics: Transportation Geography, Geographic Information Science and Systems
Keywords: VGI, crowdsourcing, data quality
Session Type: Paper
Day: 4/11/2018
Start / End Time: 8:00 AM / 9:40 AM
Room: Mid-City, Sheraton, 8th Floor
Presentation File: No File Uploaded


Information about bicycle volumes is critical for planning bicycle infrastructure. Social fitness applications are increasingly popular and provide near-continuous crowdsourced data accross the transportation network. We present an approach using Strava Metro to classify bicycle activity using spatial and temporal dynamics in rider volumes. This approach reveals dynamics within the transportation network beyond the official count stations, considers daily and seasonal patterns, and addresses increasing application popularity and the representation of sport cyclists to broader ridership. Within appropriate constraints, data from social fitness applications may provide a promissing complementary data source of information for bicycle infrastructure planning.

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