Publikation:

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

Vorschaubild

Dateien

Senaratne_2-16jjkfvirxtwr0.pdf
Senaratne_2-16jjkfvirxtwr0.pdfGröße: 484.23 KBDownloads: 846

Datum

2018

Autor:innen

Mueller, Manuel
Lalanne, Felipe
Bustos-Jimenez, Javier
Schneidewind, Jörn

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
http://nbn-resolving.de/urn:nbn:de:bsz:352-2-16jjkfvirxtwr0
DOI (zitierfähiger Link)
https://doi.org/10.1109/TITS.2017.2727281
ArXiv-ID

Internationale Patentnummer

Link zur Lizenz
Urheberrechtlich geschützt

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Open Access Green

Sammlungen

Informatik und Informationswissenschaft: Publikationen
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen 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.2017.2727281

Zusammenfassung

Urban 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.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Visual analytics, mobile network data, urban dynamics, spatial and temporal patterns, mobility, intelligent transportation system

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690SENARATNE, 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.2017.2727281
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}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/41300">
    <dc:creator>Schreck, Tobias</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:rights>terms-of-use</dc:rights>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/41300/1/Senaratne_2-16jjkfvirxtwr0.pdf"/>
    <dc:creator>Behrisch, Michael</dc:creator>
    <dc:language>eng</dc:language>
    <dc:contributor>Senaratne, Hansi</dc:contributor>
    <dcterms:title>Urban Mobility Analysis With Mobile Network Data : A Visual Analytics Approach</dcterms:title>
    <dc:contributor>Schreck, Tobias</dc:contributor>
    <dc:contributor>Lalanne, Felipe</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-02-13T12:04:10Z</dc:date>
    <dc:creator>Bustos-Jimenez, Javier</dc:creator>
    <dc:contributor>Behrisch, Michael</dc:contributor>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/41300/1/Senaratne_2-16jjkfvirxtwr0.pdf"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Mueller, Manuel</dc:creator>
    <dc:creator>Lalanne, Felipe</dc:creator>
    <dc:contributor>Schneidewind, Jörn</dc:contributor>
    <dc:creator>Schneidewind, Jörn</dc:creator>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/41300"/>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <dc:creator>Senaratne, Hansi</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Mueller, Manuel</dc:contributor>
    <dcterms:issued>2018-05</dcterms:issued>
    <dcterms:abstract xml:lang="eng">Urban 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.</dcterms:abstract>
    <dc:contributor>Bustos-Jimenez, Javier</dc:contributor>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2018-02-13T12:04:10Z</dcterms:available>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Unbekannt
Diese Publikation teilen