A Clustering Refinement Approach for Revealing Urban Spatial Structure from Smart Card Data

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dc.contributor.authorTang, Liyangen
dc.contributor.authorZhao, Yangen
dc.contributor.authorTsui, Kwok-Leungen
dc.contributor.authorHe, Yuxinen
dc.contributor.authorPan, Liweien
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2020-08-21T15:05:34Zen
dc.date.available2020-08-21T15:05:34Zen
dc.date.issued2020-08-13en
dc.date.updated2020-08-21T13:50:34Zen
dc.description.abstractFacilitated by rapid development of the data-intensive techniques together with communication and sensing technology, we can take advantage of smart card data collected through Automatic Fare Collection (AFC) systems to establish connections between public transit and urban spatial structure. In this paper, with a case study on Shenzhen metro system in China, we investigate the agglomeration pattern of passenger flow among subway stations. Specifically, leveraging inbound and outbound passenger flows at subway stations, we propose a clustering refinement approach based on cluster member stability among multiple clusterings produced by isomorphic or heterogeneous clusterers. Furthermore, we validate and elaborate five clusters of subway stations in terms of regional functionality and urban planning by comparing station clusters with reference to government planning policies and regulations of Shenzhen city. Additionally, outlier stations with ambiguous functionalities are detected using proposed clustering refinement framework.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationTang, L.; Zhao, Y.; Tsui, K.L.; He, Y.; Pan, L. A Clustering Refinement Approach for Revealing Urban Spatial Structure from Smart Card Data. Appl. Sci. 2020, 10, 5606.en
dc.identifier.doihttps://doi.org/10.3390/app10165606en
dc.identifier.urihttp://hdl.handle.net/10919/99824en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectclusteringen
dc.subjectcluster ensembleen
dc.subjectsmart card dataen
dc.subjectAFC dataen
dc.subjectpassenger flowen
dc.subjecturban spatial structureen
dc.titleA Clustering Refinement Approach for Revealing Urban Spatial Structure from Smart Card Dataen
dc.title.serialApplied Sciencesen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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