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Profiling the Dynamic Pattern of Bike-sharing Stations: a case study of Citi Bike in New York City

Liu, Y; Chen, M; Arribas-Bel, D; Singleton, A; (2021) Profiling the Dynamic Pattern of Bike-sharing Stations: a case study of Citi Bike in New York City. In: Proceedings of the 29th Annual GIS Research UK Conference (GISRUK). : Online. Green open access

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Abstract

This research applies a hierarchical k-means clustering method on the TF-IDF weighted 2019 cycling transactions from the Citi Bike bike-sharing system operating in New York City, with the primary goal of investigating the spatiotemporal usage pattern of its docking points. With a particular focus on bike-sharing stations in Manhattan, we classify 504 stations into four main clusters featuring heterogeneous dynamic usages, including leisure-oriented, residentialoriented, workplace-oriented, and off-peak oriented. We interpret each cluster based on their salient characteristics and anticipate possible future directions of this work.

Type: Proceedings paper
Title: Profiling the Dynamic Pattern of Bike-sharing Stations: a case study of Citi Bike in New York City
Event: 29th Annual GIS Research UK Conference (GISRUK)
Location: Cardiff
Dates: 14 April 2021 - 16 April 2021
Open access status: An open access version is available from UCL Discovery
DOI: 10.5281/zenodo.4665706
Publisher version: http://dx.doi.org/10.5281/zenodo.4665706
Language: English
Additional information: This article is published under a Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/legalcode)
Keywords: Bike-sharing, Mobility, Public Transit, Urban Dynamics, Spatiotemporal Data Mining
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography
URI: https://discovery.ucl.ac.uk/id/eprint/10126246
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