Ager, Alan A. and Preisler, Haiganoush K. and Arca, Bachisio and Spano, Donatella Emma Ignazia and Salis, Michele (2014) Wildfire risk estimation in the Mediterranean area. Environmetrics, Vol. 25 (6), p. 384-396. eISSN 1099-095X. Article.
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We analyzed wildland fire occurrence and size data from Sardinia, Italy, and Corsica, France, to examine spatiotemporal patterns of fire occurrence in relation to weather, land use, anthropogenic features, and time of year. Fires on these islands are largely human caused and can be attributed to negligence, agro-pastoral land use, and arson. Of particular interest was the predictive value of a fire weather index (FWI) that is widely used by fire managers to alert suppression crews. We found that an increase in the FWI from 30 to 60 produced on average an approximate eightfold increase in the odds of a large fire, regardless of the time of year during the fire season or land use type. Total area burned per fire season was positively correlated with the number of days with FWI> 40 over the period studied. Strong interactions between time of year and land type were also observed for both the probability of ignition and large fire. For example, the estimated odds of a large fire on agricultural lands in southern Sardinia was approximately 10 times larger than the forest and shrubland land type for areas close to roads, early (May) in the fire season. Conversely, toward the end of the fire season (September), we estimated the odds of a large fire in these same areas at about half the value estimated for the forest land classes. Of the explanatory variables analyzed, only FWI had an effect on the probability of a large fire (P <0.1). The results of the study can be used in several ways including the following: (1) allocating fire detection and suppression resources to specific locations during the fire season; (2) prioritizing fuel breaks along specific road segments that have high predicted ignition rates; (3) refining the current fire danger indices; and (4) parameterizing wildfire simulation models to test how changing land use and climate change may affect spatial patterns in burn probability and intensity.
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