This paper focuses on the effect of natural disasters on the population density transition. Emergency management needs demand forecasting by understanding the major demands during a disaster event. Mobile phone traffic is useful for understanding the demands because the behavioral dataset from typical surveys for ordinary demand pattern is impractical. The aim of our spatio-temporal analysis is to identify the characteristics of the population density after a disaster. To deal with this problem, we apply the latest spatial statistic approach to the aggregated mobile phone data before and after a disaster. A regression analysis clarifies the effect of the damage based on the result obtained by this approach. Our case study analyzes the population density before and after the 2016 Kumamoto earthquake. We confirm that this approach can identify the main characteristics: commuting transitions during morning and recreation population on the weekend using the data before the earthquake. The results clearly highlight some interesting spatio-temporal patterns after the earthquake: the recovery process of daily life and time variation of the refugee population density.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Spatio-Temporal Analysis for Understanding the Traffic Demand After the 2016 Kumamoto Earthquake Using Mobile Usage Data


    Beteiligte:
    Urata, Junji (Autor:in) / Sasaki, Yasushi (Autor:in) / Iryo, Takamasa (Autor:in)


    Erscheinungsdatum :

    2018-11-01


    Format / Umfang :

    2953460 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Defining Traffic States using Spatio-temporal Traffic Graphs

    Roy, Debaditya / Kumar, K. Naveen / Mohan, C. Krishna | IEEE | 2020


    DISASTER COUNTERMEASURE EXPERIMENTS USING WINDS AND THE RESPONSE OF 2016 KUMAMOTO EARTHQUAKES

    Jeong, Byeongpyo / Susukita, Hajime / Kan, Tomoshige et al. | TIBKAT | 2021


    Ferienhütte bei Kumamoto

    Geipel, Kaye | Online Contents | 2009



    Virtualized Traffic: Reconstructing Traffic Flows from Discrete Spatio-Temporal Data

    van den Berg, Jur / Sewall, Jason / Lin, Ming et al. | IEEE | 2009