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Article: Exploratory calibration of a spatial interaction model using taxi GPS trajectories
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TitleExploratory calibration of a spatial interaction model using taxi GPS trajectories
 
AuthorsYue, Y3 2
Wang, HD3 2
Hu, B3 2
Li, QQ3 2
Li, YG3 2
Yeh, AGO1
 
KeywordsGPS data
Model calibration
Spatial interaction model
Trading area analysis
Trajectory analysis
 
Issue Date2012
 
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/ceus
 
CitationComputers, Environment And Urban Systems, 2012, v. 36 n. 2, p. 140-153 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.compenvurbsys.2011.09.002
 
AbstractModel calibration is the cornerstone of spatial interaction models in many geographic, transportation and marketing analysis. Conventional questionnaire approaches that collect data for model calibration are both labor-intensive and time-consuming, and generally show a poor response rate. This study takes advantage of increasingly available vehicle GPS trajectory data to conduct spatial interaction model calibration. A Huff model for retail trading area analysis was used as an example. Model calibration and parameter validation were conducted based on over 63,000 taxi GPS trajectories for seven major shopping centers in Wuhan, a large city in China. The results were positive and in general showed satisfactory descriptive and predictive capability. This study demonstrated the feasibility of using the emerging technology to calibrate spatial interaction models (and also showed the potential for use in other related studies). The main advantage of using these new data sources is that they allow efficient use of increasingly available positioning data, which is easier to collect than conventional customer surveys, and usually with larger data sizes. It also allows inferences to be made about distance-decay rates based on accurate computation of travel time and distance. This could save both time and expense in many related areas of research, while achieving high quality model calibration results. © 2011 Elsevier Ltd.
 
ISSN0198-9715
2013 Impact Factor: 1.520
2013 SCImago Journal Rankings: 1.079
 
DOIhttp://dx.doi.org/10.1016/j.compenvurbsys.2011.09.002
 
ISI Accession Number IDWOS:000302488500005
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorYue, Y
 
dc.contributor.authorWang, HD
 
dc.contributor.authorHu, B
 
dc.contributor.authorLi, QQ
 
dc.contributor.authorLi, YG
 
dc.contributor.authorYeh, AGO
 
dc.date.accessioned2012-09-20T08:28:13Z
 
dc.date.available2012-09-20T08:28:13Z
 
dc.date.issued2012
 
dc.description.abstractModel calibration is the cornerstone of spatial interaction models in many geographic, transportation and marketing analysis. Conventional questionnaire approaches that collect data for model calibration are both labor-intensive and time-consuming, and generally show a poor response rate. This study takes advantage of increasingly available vehicle GPS trajectory data to conduct spatial interaction model calibration. A Huff model for retail trading area analysis was used as an example. Model calibration and parameter validation were conducted based on over 63,000 taxi GPS trajectories for seven major shopping centers in Wuhan, a large city in China. The results were positive and in general showed satisfactory descriptive and predictive capability. This study demonstrated the feasibility of using the emerging technology to calibrate spatial interaction models (and also showed the potential for use in other related studies). The main advantage of using these new data sources is that they allow efficient use of increasingly available positioning data, which is easier to collect than conventional customer surveys, and usually with larger data sizes. It also allows inferences to be made about distance-decay rates based on accurate computation of travel time and distance. This could save both time and expense in many related areas of research, while achieving high quality model calibration results. © 2011 Elsevier Ltd.
 
dc.description.naturelink_to_subscribed_fulltext
 
dc.identifier.citationComputers, Environment And Urban Systems, 2012, v. 36 n. 2, p. 140-153 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.compenvurbsys.2011.09.002
 
dc.identifier.citeulike9999074
 
dc.identifier.doihttp://dx.doi.org/10.1016/j.compenvurbsys.2011.09.002
 
dc.identifier.epage153
 
dc.identifier.hkuros210512
 
dc.identifier.isiWOS:000302488500005
 
dc.identifier.issn0198-9715
2013 Impact Factor: 1.520
2013 SCImago Journal Rankings: 1.079
 
dc.identifier.issue2
 
dc.identifier.openurl
 
dc.identifier.scopuseid_2-s2.0-84858026248
 
dc.identifier.spage140
 
dc.identifier.urihttp://hdl.handle.net/10722/166092
 
dc.identifier.volume36
 
dc.languageeng
 
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/ceus
 
dc.publisher.placeUnited Kingdom
 
dc.relation.ispartofComputers, Environment and Urban Systems
 
dc.relation.referencesReferences in Scopus
 
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [VOL#, ISSUE#, (DATE)] DOI#
 
dc.subjectGPS data
 
dc.subjectModel calibration
 
dc.subjectSpatial interaction model
 
dc.subjectTrading area analysis
 
dc.subjectTrajectory analysis
 
dc.titleExploratory calibration of a spatial interaction model using taxi GPS trajectories
 
dc.typeArticle
 
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Author Affiliations
  1. The University of Hong Kong
  2. Wuhan University
  3. Ministry of Education China