The growing need to address natural and human-induced disasters while protecting territory remains a key focus for the scientific community. Effective emergency management, especially during wildfires, requires coordinated responses to safeguard lives and assets. This study develops hazard maps to aid emergency planning in Italy and estimate territorial resilience indicators. Focusing on wildfire ignition hazards in Ischia, the study uses a probabilistic model based on fifteen years of wildfire data (2009–2023). By analyzing ignition points and employing a Poisson distribution, it correlates ignition probabilities with vegetation types. The hazard maps reveal that wildfire risk is primarily influenced by the wildland–urban interface and vegetation characteristics, emphasizing the need to integrate territorial and urban factors into wildfire forecasting. The findings also suggest areas for refining the model to enhance risk mitigation strategies.
Forecasting of Wildfire Probability Occurrence: Case Study of a Mediterranean Island of Italy / Berardi, Davide; Galuppi, Marta; Libertà, Angelo; Lombardi, Mara. - In: LAND. - ISSN 2073-445X. - 14:2(2025). [10.3390/land14020277]
Forecasting of Wildfire Probability Occurrence: Case Study of a Mediterranean Island of Italy
Davide BerardiPrimo
;Marta Galuppi
;Mara Lombardi
2025
Abstract
The growing need to address natural and human-induced disasters while protecting territory remains a key focus for the scientific community. Effective emergency management, especially during wildfires, requires coordinated responses to safeguard lives and assets. This study develops hazard maps to aid emergency planning in Italy and estimate territorial resilience indicators. Focusing on wildfire ignition hazards in Ischia, the study uses a probabilistic model based on fifteen years of wildfire data (2009–2023). By analyzing ignition points and employing a Poisson distribution, it correlates ignition probabilities with vegetation types. The hazard maps reveal that wildfire risk is primarily influenced by the wildland–urban interface and vegetation characteristics, emphasizing the need to integrate territorial and urban factors into wildfire forecasting. The findings also suggest areas for refining the model to enhance risk mitigation strategies.File | Dimensione | Formato | |
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