The increasing incidence of wildfires in the Mediterranean region has raised significant scientific and environmental concerns. This study focuses on a retrospective analysis of wildfire ignition and propagation within the context of the Monte Catillo Natural Reserve in Italy. After conducting a comprehensive review of the current state-of-the-art wildfire susceptibility mapping, propagation modeling, probability assessment, forest vulnerability models, and preventive silvicultural measures, we examine the regulatory framework surrounding wildfires in the national context, with a specific focus on prevention, prediction, and active firefighting measures. A geostatistical model of wildfire occurrence was developed, starting with the characterization of the area vegetation and anthropogenic factors influencing wildfire ignition. After that, wildfire observations from the period between 2010 and 2021 were included. The objective is to generate a wildfire hazard map for two distinct vegetation communities. To accomplish this, a statistical analysis was applied using the Poisson Model, assessing its goodness-of-fit by comparing observed frequencies with experimental data through the chi-square test. In conclusion, this model serves as a valuable tool for characterizing wildfire hazards, including ignition probabilities and propagation scenarios, within the Monte Catillo Natural Reserve. The research significantly contributes to enhancing our understanding of wildfire dynamics and plays a crucial role in the development of effective strategies for wildfire risk management.

Geostatistical Modeling of Wildfire Occurrence Probability. The Case Study of Monte Catillo Natural Reserve in Italy / Berardi, Davide; Galuppi, Marta; Libertà, Angelo; Lombardi, Mara. - In: FIRE. - ISSN 2571-6255. - 6:11(2023), pp. 427-450. [10.3390/fire6110427]

Geostatistical Modeling of Wildfire Occurrence Probability. The Case Study of Monte Catillo Natural Reserve in Italy

Davide Berardi
Primo
;
Marta Galuppi
Secondo
;
Mara Lombardi
Ultimo
2023

Abstract

The increasing incidence of wildfires in the Mediterranean region has raised significant scientific and environmental concerns. This study focuses on a retrospective analysis of wildfire ignition and propagation within the context of the Monte Catillo Natural Reserve in Italy. After conducting a comprehensive review of the current state-of-the-art wildfire susceptibility mapping, propagation modeling, probability assessment, forest vulnerability models, and preventive silvicultural measures, we examine the regulatory framework surrounding wildfires in the national context, with a specific focus on prevention, prediction, and active firefighting measures. A geostatistical model of wildfire occurrence was developed, starting with the characterization of the area vegetation and anthropogenic factors influencing wildfire ignition. After that, wildfire observations from the period between 2010 and 2021 were included. The objective is to generate a wildfire hazard map for two distinct vegetation communities. To accomplish this, a statistical analysis was applied using the Poisson Model, assessing its goodness-of-fit by comparing observed frequencies with experimental data through the chi-square test. In conclusion, this model serves as a valuable tool for characterizing wildfire hazards, including ignition probabilities and propagation scenarios, within the Monte Catillo Natural Reserve. The research significantly contributes to enhancing our understanding of wildfire dynamics and plays a crucial role in the development of effective strategies for wildfire risk management.
2023
wildfire; season trends; probability; geostatistical model; Poisson; fire ignition; qgis map; climate change
01 Pubblicazione su rivista::01a Articolo in rivista
Geostatistical Modeling of Wildfire Occurrence Probability. The Case Study of Monte Catillo Natural Reserve in Italy / Berardi, Davide; Galuppi, Marta; Libertà, Angelo; Lombardi, Mara. - In: FIRE. - ISSN 2571-6255. - 6:11(2023), pp. 427-450. [10.3390/fire6110427]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1691612
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