Abstract
The risk of forest fires is a major problem in Türkiye's Mediterranean region and has a significant impact on ecosystems and atmospheric conditions. Throughout the previous century, a significant portion of Türkiye's Mediterranean Region has been destroyed by forest fires. This study aims to determine the meteorological covariates, such as relative humidity, maximum temperature, and wind speed, that affect forest fires. We classified forest fires into two groups. The first group (F1) refers to small forest fires, with burned forest areas of less than 10 hectares. The second group (F2), representing rare events, corresponds to burned areas of more than 10 hectares. The data is composed of binary values (F1=0 and F2=1) taken between the years 2015-2019 from different locations in the Mediterranean Region of Türkiye. For binary data modeling, the ordinary logistic regression (LR) has been frequently used. However, such a method tends to give biased results when using rare event data. Therefore, we employed three different modeling techniques specifically designed for rare event data. According to the results obtained from the best model, Firth's Logistic Regression (FLR), wind speed, and maximum temperature are found to be statistically significant variables in the occurrence of forest fires greater than 10 hectares.
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