Tom De Groeve, Luca Vernaccini, & Alessandro Annunziato. (2006). Modelling disaster impact for the global disaster alert and coordination system. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 409–417). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: The Global Disaster Alert and Coordination System, jointly developed by the European Commission and the United Nations, combines existing web-based disaster information management systems with the aim to alert the international community in case of major sudden-onset disasters and to facilitate the coordination of international response during the relief phase of the disaster. The disaster alerts are based on automatic hazard information retrieval and real-time running of impact models. This paper describes impact models for earthquakes, tsunamis and tropical cyclones.
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Rajius Idzalika, Yulistina Riyadi, Imaduddin Amin, George Hodge, & Jong Gun Lee. (2019). Understanding Aggregate Human Behaviour Changes in Response to a Natural Disaster in Vanuatu via Mobile Network Data Analysis. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: This paper presents a use case of mobile network data as a new source of insight for humanitarian action. Based on analysis covering the Republic of Vanuatu, we identify aggregate behavioral patterns indicating short term and medium term behavior changes as a result of a tropical cyclone, which could contribute to our understanding of the resilience of communities to natural hazards. We also find interesting behavioral insights on how the human movement network is impacted by a cyclone. Due to the detail and tractability of the data set, insights on preparation, displacement, damage and resilience could enable more agile and adaptive responses by public institutions and other actors to humanitarian emergencies. Considering the array of natural hazards that the South Pacific region faces on an annual basis, this use case contributes more evidence in favor of using anonymized mobile network data to inform humanitarian action.
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Yan Wang, Qi Wang, & John Taylor. (2021). Loss of Resilience in Human Mobility across Severe Tropical Cyclones of Different Magnitudes. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 755–765). Blacksburg, VA (USA): Virginia Tech.
Abstract: Severe tropical cyclones impose threats on highly populated coastal urban areas, thereby, understanding and predicting human movements plays a critical role in evaluating disaster resilience of human society. However, limited research has focused on tropical cyclones and their influence on human mobility resilience. This preliminary study examined the strength and duration of human mobility perturbation across five significant tropical storms and their affected eight urban areas using Twitter data. The results suggest that tropical cyclones can significantly perturb human movements by changing travel frequencies and displacement probability distributions. While the power-law still best described the pattern of human movements, the changes in the radii of gyration were significant and resulted in perturbation and loss of resilience in human mobility. The findings deepen the understanding about human-environment interactions under extreme events, improve our ability to predict human movements using social media data, and help policymakers improve disaster evacuation and response.
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