Urban Mobility Analysis With Mobile Network Data : A Visual Analytics Approach

dc.contributor.authorSenaratne, Hansi
dc.contributor.authorMueller, Manuel
dc.contributor.authorBehrisch, Michael
dc.contributor.authorLalanne, Felipe
dc.contributor.authorBustos-Jimenez, Javier
dc.contributor.authorSchneidewind, Jörn
dc.contributor.authorKeim, Daniel A.
dc.contributor.authorSchreck, Tobias
dc.date.accessioned2018-02-13T12:04:10Z
dc.date.available2018-02-13T12:04:10Z
dc.date.issued2018-05
dc.description.abstractUrban planning and intelligent transportation management are facing key challenges in today's ever more urbanized world. Providing the right tools to city planners is crucial to cope with these challenges. Data collected from citizens' mobile communication can be used as the foundation for such tools. These kinds of data can facilitate various analysis tasks, such as the extraction of human movement patterns or determining the urban dynamics of a city. City planners can closely monitor such patterns based on which strategic decisions can be taken to improve a city's infrastructure. In this paper, we introduce a novel visual analytics approach for pattern exploration and search in global system for mobile communications mobile networks. We define geospatial and matrix representations of data, which can be interactively navigated. The approach integrates data visualization with suitable data analysis algorithms, allowing to spatially and temporally compare mobile usage, identify regularities, as well as anomalies in daily mobility patterns across regions and user groups. As an extension to our visual analytics approach, we further introduce space-time prisms with uncertain markers to visually analyze the uncertainty of urban mobility patterns.eng
dc.description.versionpublishedeng
dc.identifier.doi10.1109/TITS.2017.2727281eng
dc.identifier.ppn1665890495
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/41300
dc.language.isoengeng
dc.rightsterms-of-use
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subjectVisual analytics, mobile network data, urban dynamics, spatial and temporal patterns, mobility, intelligent transportation systemeng
dc.subject.ddc004eng
dc.titleUrban Mobility Analysis With Mobile Network Data : A Visual Analytics Approacheng
dc.typeJOURNAL_ARTICLEeng
dspace.entity.typePublication
kops.citation.bibtex
@article{Senaratne2018-05Urban-41300,
  year={2018},
  doi={10.1109/TITS.2017.2727281},
  title={Urban Mobility Analysis With Mobile Network Data : A Visual Analytics Approach},
  number={5},
  volume={19},
  issn={1524-9050},
  journal={IEEE Transactions on Intelligent Transportation Systems},
  pages={1537--1546},
  author={Senaratne, Hansi and Mueller, Manuel and Behrisch, Michael and Lalanne, Felipe and Bustos-Jimenez, Javier and Schneidewind, Jörn and Keim, Daniel A. and Schreck, Tobias}
}
kops.citation.iso690SENARATNE, Hansi, Manuel MUELLER, Michael BEHRISCH, Felipe LALANNE, Javier BUSTOS-JIMENEZ, Jörn SCHNEIDEWIND, Daniel A. KEIM, Tobias SCHRECK, 2018. Urban Mobility Analysis With Mobile Network Data : A Visual Analytics Approach. In: IEEE Transactions on Intelligent Transportation Systems. 2018, 19(5), pp. 1537-1546. ISSN 1524-9050. eISSN 1558-0016. Available under: doi: 10.1109/TITS.2017.2727281deu
kops.citation.iso690SENARATNE, Hansi, Manuel MUELLER, Michael BEHRISCH, Felipe LALANNE, Javier BUSTOS-JIMENEZ, Jörn SCHNEIDEWIND, Daniel A. KEIM, Tobias SCHRECK, 2018. Urban Mobility Analysis With Mobile Network Data : A Visual Analytics Approach. In: IEEE Transactions on Intelligent Transportation Systems. 2018, 19(5), pp. 1537-1546. ISSN 1524-9050. eISSN 1558-0016. Available under: doi: 10.1109/TITS.2017.2727281eng
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