Using a GIS-based spatial approach to determine the optimal locations of bikeshare stations: The case of Washington D.C

Zhila Dehdari Ebrahimi, Mohsen Momenitabar, Arefeh A. Nasri and Jeremy Mattson

Transport Policy, 2022, vol. 127, issue C, 48-60

Abstract: Today, the number of cities implementing bike-share programs is remarkably increasing. One of the critical elements of implementing a successful bike-share program is integrating it with other transportation modes such as bus and metro and extending its coverage in high-density residential and employment areas to encourage more demand. In this study, we utilize a GIS-based method to visualize the spatial distribution of bike-share stations using the location-allocation problem, using the Capital bike-share program in Washington D.C. metropolitan areas as a study area. We chose Washington D.C. as it was one of the first cities in the United States that launched a bike-share program and currently has one of the largest bike-share systems across the country. The location-allocation problem, including Target Market Share (TMS) and Maximize Coverage and Minimize Facility (MCMF), is considered to analyze the accessibility of promoting transit modes with bike-share systems across the District of Columbia. Location-allocation models are investigated to determine the potential bike station locations accessible to the maximum population and within a 300-m buffer around public transit stations (e.g., bus, metro). The results show that the bike-share system in Washington D.C. is more accessible for transit users as an access/egress mode. At the same time, in areas farther away from downtown D.C., docking stations are more distanced apart and offer less coverage, especially in residential-only areas. Finally, our methodology can potentially be utilized for optimal station location allocation in any other city where maximum exposure is required.

Keywords: Bike-share program; Public transit; Location-allocation model; GIS; Washington D.C (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tranpol.2022.08.008

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