Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81733
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorHuang, JWen_US
dc.creatorLiu, XTen_US
dc.creatorZhao, PXen_US
dc.creatorZhang, JWen_US
dc.creatorKwan, MPen_US
dc.date.accessioned2020-02-10T12:28:53Z-
dc.date.available2020-02-10T12:28:53Z-
dc.identifier.urihttp://hdl.handle.net/10397/81733-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Huang, J.; Liu, X.; Zhao, P.; Zhang, J.; Kwan, M.-P. Interactions between Bus, Metro, and Taxi Use before and after the Chinese Spring Festival. ISPRS Int. J. Geo-Inf. 2019, 8, 445, 1-18 is available at https://dx.doi.org/10.3390/ijgi8100445en_US
dc.subjectSmart card dataen_US
dc.subjectTaxi gPS trajectoriesen_US
dc.subjectPublic transport modesen_US
dc.subjectTravel behavioren_US
dc.subjectBuilt environmenten_US
dc.titleInteractions between bus, metro, and taxi use before and after the Chinese spring festivalen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage18en_US
dc.identifier.volume8en_US
dc.identifier.issue10en_US
dc.identifier.doi10.3390/ijgi8100445en_US
dcterms.abstractPublic transport plays an important role in developing sustainable cities. A better understanding of how different public transit modes (bus, metro, and taxi) interact with each other will provide better sustainable strategies to transport and urban planners. However, most existing studies are either limited to small-scale surveys or focused on the identification of general interaction patterns during times of regular traffic. Transient demographic changes in a city (i.e., many people moving out and in) can lead to significant changes in such interaction patterns and provide a useful context for better investigating the changes in these patterns. Despite that, little has been done to explore how such interaction patterns change and how they are linked to the built environment from the perspective of transient demographic changes using urban big data. In this paper, the tap-in-tap-out smart card data of bus/metro and taxi GPS trajectory data before and after the Chinese Spring Festival in Shenzhen, China, are used to explore such interaction patterns. A time-series clustering method and an elasticity change index (ECI) are adopted to detect the changing transit mode patterns and the underlying dynamics. The findings indicate that the interactions between different transit modes vary over space and time and are competitive or complementary in different parts of the city. Both ordinary least-squares (OLS) and geographically weighted regression (GWR) models with built environment variables are used to reveal the impact of changes in different transit modes on ECIs and their linkage with the built environment. The results of this study will contribute to the planning and design of multi-modal transport services.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationISPRS international journal of geo-information, 10 Oct. 2019, v. 8, no. 10, 445, p. 1-18en_US
dcterms.isPartOfISPRS international journal of geo-informationen_US
dcterms.issued2019-
dc.identifier.isiWOS:000498398300020-
dc.identifier.scopus2-s2.0-85097857944-
dc.identifier.eissn2220-9964en_US
dc.identifier.artn445en_US
dc.description.validate202002 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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