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A CELLULAR AUTOMATA METHODOLOGY FOR EVALUATING LAVA FLOW HAZARD AT MOUNT ETNA ( ITALY )

Different worldwide volcanic areas are densely populated and urbanized. For instance, in Italy, despite being the most active volcano in Europe, Mt Etna is home to approximately one million people. During the last decades, the vulnerability of the Etnean area has increased exponentially due to continued, at times wild, urbanization, with the consequence that new eruptions may involve even greater risks. A modern and widely adopted approach to access the impact and individuate affected areas of future events is the application of algorithms that permit numerical simulations of lava flows. However, this modus operandi can be difficult to be replicated and an a priori knowledge of the degree of exposure of the volcano surrounding areas desirable, in order to allow both the realisation of preventive countermeasures, and a more rational land use planning. We here show results of a new methodology for the definition of flexible high-resolution lava invasion susceptibility maps, and show results and applications related to the Eastern flank of Mt Etna, the most densely populated sector of the volcano. The methodology here proposed relies on the application of SCIARA, a reliable and robust Cellular Automata lava flows computational model for simulating new events on present topographic data, and on a new criterion for evaluating the