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Geospatial Analysis to Support Urban Planning in BeijingFinding Public Transportation Community Structure Based on Large-Scale Smart Card Records in Beijing

Geospatial Analysis to Support Urban Planning in Beijing: Finding Public Transportation Community... [Public transportation in big cities is a crucial part of urban transportation infrastructures. Exploring the spatiotemporal patterns of public trips can help us to understand dynamic transportation patterns and the complex urban systems thus supporting better urban planning and design. The availability of large-scale smart card data (SCD) offers new opportunities to study intra-urban structure and spatial interaction dynamics. In this research, we applied the novel community detection methods from the study of complex networks to examine the dynamic spatial interaction structures of public transportation communities in the Beijing Metropolitan Area. It can help to find the ground-truth community structure of strongly connected traffic analysis zones by public transportation, which may yield insights for urban planners on land use patterns or for transportation engineers on traffic congestion. We also found that the daily community detection results using SCD are different from that using household travel surveys. The SCD results match better with the planned urban area boundary, which means that the actual operation data of publication transportation might be a good source to validate the urban planning and development.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Geospatial Analysis to Support Urban Planning in BeijingFinding Public Transportation Community Structure Based on Large-Scale Smart Card Records in Beijing

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References (14)

Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2015
ISBN
978-3-319-19341-0
Pages
155 –167
DOI
10.1007/978-3-319-19342-7_8
Publisher site
See Chapter on Publisher Site

Abstract

[Public transportation in big cities is a crucial part of urban transportation infrastructures. Exploring the spatiotemporal patterns of public trips can help us to understand dynamic transportation patterns and the complex urban systems thus supporting better urban planning and design. The availability of large-scale smart card data (SCD) offers new opportunities to study intra-urban structure and spatial interaction dynamics. In this research, we applied the novel community detection methods from the study of complex networks to examine the dynamic spatial interaction structures of public transportation communities in the Beijing Metropolitan Area. It can help to find the ground-truth community structure of strongly connected traffic analysis zones by public transportation, which may yield insights for urban planners on land use patterns or for transportation engineers on traffic congestion. We also found that the daily community detection results using SCD are different from that using household travel surveys. The SCD results match better with the planned urban area boundary, which means that the actual operation data of publication transportation might be a good source to validate the urban planning and development.]

Published: May 14, 2015

Keywords: Public transportation; Smart card records; Spatial interaction; OD flow matrix; Community detection; Urban big data

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