How the COVID-19 Pandemic Affected Spatio-Temporal Usage Patterns in a Bikesharing System

Bicycle sharing became a popular mode of transportation in cities until the COVID-19 pandemic, when providers faced a loss in ridership, although cycling was recommended for social distancing. While otherbicyclc sharing systems (BSS) recovered, the BSS Capital Bikeshare (CaBi) did not. This research evaluates the spatial and temporal usage patterns of the CaBi system before and after the COVID-19 outbreak. First, publicly available raw data was analyzed with basic statistical metrics to distinguish trip frequency and duration for both periods. Second, the member type of riders andtemporal distribution of trips was analyzed. Applying the k-mcans clustering algorithm, stations with similar rental activities corresponding to the hour of the day and trip duration were categorized in the third step. Overall, it can be said that a change in temporal usage patterns of the stations has been noticed, whereas the spatial clusters did not change much during the pandemic. BSS operators and urban planners canuse such insights to enhance operations.