Classification of large wildfires in South-Eastern France to adapt suppression strategies
| Autor: | Lahaye, S., Curt, T., Paradis, L., Hély, C. |
|---|---|
| Přispěvatelé: | aucun, Service Départemental d'Incendie et de Secours des Bouches - du - Rhône, Ecosystèmes méditerranéens et risques (UR EMAX), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), Paléoenvironnement et chronoécologie UMR 5059-CNRS/Montpellier II/EPHE (PALECO), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), École Pratique des Hautes Études (EPHE), Centre de Bio-Archéologie et d'Ecologie (CBAE), Université Montpellier 2 - Sciences et Techniques (UM2)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | Advances in Forest Fire Research. Chapter 3-Fire Management Advances in Forest Fire Research. Chapter 3-Fire Management, Imprensa da Universidade de Coimbra, pp.696-708, 2014, ⟨10.14195/978-989-26-0884-6_78⟩ |
| DOI: | 10.14195/978-989-26-0884-6_78⟩ |
| Popis: | [Departement_IRSTEA]Territoires [TR1_IRSTEA]SEDYVIN; Large wildfires keep on developing in the French Mediterranean region, regularly threatening responders. We tested if these large fires could be classified into types, and if these types were representative of different environmental drivers. To proceed, we established a database comprising 153 of the largest fires from the last 25 years. For each fire we collected three datasets to describe the environment, the fire behaviour and the control operations. We performed a hierarchical clustering analysis followed by a predictive analysis with Bootstrap Regression Trees. Fires were classified in 8 types that could a posteriori be reduced to 5 types. The One-way type was featured by moderate environmental parameters, the Multi-way type was featured by slope, the Winding and Rapid types were featured by wind, while the Very large type was featured by the drought code. Moreover, the probability of having vehicles trapped in a large fire was primarily correlated with the number of vehicles assigned for suppression. This study provides the basis for upcoming trainings of Fire Analyst in France. It paves the way for further research on predictive wildfire danger mapping. |
| Databáze: | OpenAIRE |
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