The structure of spatial networks and communities in bicycle sharing systems

Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys...

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Bibliographic Details
Published in:PloS one 2013-09, Vol.8 (9), p.e74685
Main Authors: Zaltz Austwick, Martin, O'Brien, Oliver, Strano, Emanuele, Viana, Matheus
Format: Article
Language:English
Subjects:
Analysis
Bicycles
Bicycling
Bike sharing
Cities
Cluster analysis
Cooperative Behavior
Geography
Graphs
Humans
Local transit
Models, Theoretical
Network analysis
Public Facilities
Public health
Public transportation
Rankings
Residence Characteristics
Scaling
Scaling laws
Smart cities
Social networks
Spatial analysis
Statistical analysis
Transportation
Travel - statistics & numerical data
United Kingdom
United States
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Summary:Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys (start and end time and location) taking place in their bicycle sharing system. In this paper, we employ visualization, descriptive statistics and spatial and network analysis tools to explore system usage in these cities, using techniques to investigate features specific to the unique geographies of each, and uncovering similarities between different systems. Journey displacement analysis demonstrates similar journey distances across the cities sampled, and the (out)strength rank curve for the top 50 stands in each city displays a similar scaling law for each. Community detection in the derived network can identify local pockets of use, and spatial network corrections provide the opportunity for insight above and beyond proximity/popularity correlations predicted by simple spatial interaction models.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0074685