Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas char...

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Detalhes bibliográficos
Autores: Salis, Michele, Ager, Alan A., Alcasena Urdíroz, Fermín J., Arca, Bachisio, Finney, Mark A., Pellizzaro, G., Spano, Donatella
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Recursos:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/49044
Acesso em linha:https://doi.org/10.1007/s10661-014-4175-x
http://hdl.handle.net/10459.1/49044
Access Level:acceso abierto
Palavra-chave:Incendis forestals
Itàlia
Forest fires
Italy
Descrição
Resumo:In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.