Studying human movement citywide is important for understanding mobility and transportation patterns. Rather than investigating the trajectories of individuals, we employ an Eulerian approach to analyze the crowd flows among a geographical network and a social network, which are extracted from mobile phone data. We design a suite of visualization techniques to illustrate the dynamic evolutions of the flow over the networks. We contribute the design and implementation of a visual analytics system, which is called Mobility Viewer, that supports situation-aware understanding and visual reasoning of human mobility. We exemplify our approach with a real citywide data set of seven million users in two months.


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    Titel :

    Mobility Viewer: An Eulerian Approach for Studying Urban Crowd Flow


    Beteiligte:
    Ma, Yuxin (Autor:in) / Lin, Tao (Autor:in) / Cao, Zhendong (Autor:in) / Li, Chen (Autor:in) / Wang, Fei (Autor:in) / Chen, Wei (Autor:in)


    Erscheinungsdatum :

    2016-09-01


    Format / Umfang :

    2028365 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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