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The Crisis Classification Component to Strengthen the Early Warning, Risk Assessment and Decision Support in Extreme Climate Events

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Dynamics of Disasters

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 169))

Abstract

Climate change is considered as being one of the most important challenges of modern times, having multiple and significant impacts on human societies and environment. The negative effects which are revealed through weather extreme events and causing distress and loss of property and human lives will become more intensive in the future, especially in poor countries. Hence, there is an urgent need to develop novelty tools to enhance awareness and preparedness, to assess risks and to support decision-making, aiming to increase the social resilience to climate changes.

The proposed open-source holistic beAWARE framework encompasses technological achievements that enables first responders and authorities to manage efficiently the pre-emergency and emergency phases of a hazardous natural event. Specifically, the Crisis Classification component of beAWARE platform consolidates functionalities to provide dual services: (a) firstly, as an Early-Warning system, aiming to estimate the crisis level of the upcoming extreme conditions such as the hazard of flood, fire or heatwave (pre-emergency phase), and (b) secondly, as a Real-Time Monitoring and Risk Assessment system aiming to assess the risk and support to make accurate and timely decisions, when a crisis has evolved.

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Acknowledgements

This work was supported by the EC-funded research and innovation program H2020 beAWARE: “Enhancing decision support and management services in extreme weather climate events” under the grant agreement No.700475.

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Authors and Affiliations

  1. Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thermi-Thessaloniki, Greece

    Gerasimos Antzoulatos, Anastasios Karakostas, Stefanos Vrochidis & Ioannis Kompatsiaris

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  1. Gerasimos Antzoulatos
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  2. Anastasios Karakostas
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  3. Stefanos Vrochidis
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  4. Ioannis Kompatsiaris
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Correspondence to Gerasimos Antzoulatos .

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Editors and Affiliations

  1. Department of Physics & Computer Science, Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias S. Kotsireas

  2. Isenberg School of Management, University of Massachusetts Amherst , Amherst, MA, USA

    Anna Nagurney

  3. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  4. University of Florida, Gainesville, FL, USA

    Arsenios Tsokas

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Antzoulatos, G., Karakostas, A., Vrochidis, S., Kompatsiaris, I. (2021). The Crisis Classification Component to Strengthen the Early Warning, Risk Assessment and Decision Support in Extreme Climate Events. In: Kotsireas, I.S., Nagurney, A., Pardalos, P.M., Tsokas, A. (eds) Dynamics of Disasters. Springer Optimization and Its Applications, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-030-64973-9_3

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