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A Crisis Classification System for flood risk assessment: the beAWARE project

Authors: Antzoulatos, Gerasimos; Karakostas, Anastasios; Vrochidis, Stefanos; Kompatsiaris, Ioannis; Lombardo, Francesca; Norbiato, Danielle; Ferri, Michele;

A Crisis Classification System for flood risk assessment: the beAWARE project

Abstract

Crisis management is a dynamic, complex and multi-disciplinary process, consisting of consecutive sets of activities to collect information, analyse heterogeneous data, formulate alternatives, decision-making processes, implementation, and monitoring. Especially, in the content of the natural disaster the emergence of numerous Early Warning systems and specialised Decision Support Systems (DSS) plays an important role in assisting to reduce the risks resulting from the interaction of human societies and their natural environments. Currently, the majority of these emerged tools are not capable to provide an integrated and generalised framework for formulating decision options for crisis level estimation and risk assessment. Furthermore, the advances to the IoT as well as the increasingly volume of heterogeneous data from multiple resources (mobile phones and Apps, sensory data, drones etc) generate new capabilities and opportunities to timely alerting and tackling effectively an extreme weather or natural phenomenon. The authorities and decision makers should confront new challenges in flood risk management by operating in a holistic and interoperable framework combining data from multiple resources. A few efforts are towards on this direction by proposing generalised platforms combining the flood risk management relevant science, such as FLOODSS.

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Keywords

Real-time Monitoring and Risk Assessment DSS, Flood hazard, Flood Management, Early Warning System

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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