Valutazione della predisposizione all'incendio boschivo a scala regionale: una modellazione per misure di mitigazione ambientale

Mattia Cugini (a), Sara Mandelli (b), Debora Voltolina (b), Giacomo Cappellini (a), Gloria Bordogna (a) & Simone Sterlacchini (a)
(a) National Research Council of Italy, Institute for the Dynamics of Environmental Processes, Piazza della Scienza 1, 20126, Milan, Italy. E-mail: mattia.cugini@gmail.com (b) University of Milan, Natural Sciences Department, Via Festa del Perdono 7, 20122, Milan, Italy.

Wildfires play a crucial role in landscape transformation and soil degradation processes. Urban areas, settlements and infrastructure are increasingly exposed to wildfire threats because of their progressive expansion, potentially leading to significant economic losses. The purpose of this study is the application and calibration of different models and algorithms, applied at different scales, for preparedness and response to wildfire disaster-related activities. In more detail, wildfire ignition is assessed by the Weights of Evidence modeling technique; wildfire spreading is analyzed by applying two different modeling techniques: the former is based on the GRASS GIS heuristic algorithms (r.ros and r.spread); the latter on a genetic algorithm. All the models applied are calibrated on historical databases concerning past events and results are critically compared.

fire spreading, genetic algorithm, GRASS GIS heuristic algorithms, wildfire hazard and risk.