A NEW APPROACH TO DETERMINE THE INFLUENCE OF WEATHER CONDITIONS ON FOREST FIRE RISK IN THE MEDITERRANEAN REGION OF TÜRKİYE

Öz

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.

Anahtar Kelimeler

• Climate Change
• Humidity
• Natural Hazard
• Penalized Regression

TÜRKİYE'NIN AKDENIZ BÖLGESINDE HAVA KOŞULLARININ ORMAN YANGIN RISKINE ETKISINI BELIRLEMEYE YÖNELIK YENI BIR YAKLAŞIM

Öz

Orman yangınları riski, Türkiye'nin Akdeniz bölgesinde önemli bir sorundur ve ekosistemlere ile atmosferik özelliklere büyük etkisi vardır. Geçmiş yüzyıl boyunca Türkiye'nin Akdeniz Bölgesi'nin büyük bir kısmı orman yangınları sonucunda tahrip olmuştur. Bu çalışma, orman yangınlarını etkileyen bağıl nem, maksimum sıcaklık ve rüzgâr hızı gibi meteorolojik değişkenleri belirlemeyi amaçlamaktadır. Orman yangınlarını iki gruba ayırdık. Birinci grup (F1), 10 hektardan küçük yanmış orman alanlarını ifade eder. Nadir olayları temsil eden ikinci grup (F2), 10 hektardan fazla yanmış alanları temsil eder. Veriler, Türkiye'nin Akdeniz Bölgesi'ndeki farklı lokasyonlardan 2015-2019 yılları arasında alınan ikili değerlerden oluşmaktadır (F1=0 ve F2=1). İkili veri modellemesi için, genellikle sıradan lojistik regresyon (LR) kullanılmaktadır. Ancak, nadir olay verileri kullanıldığında bu yöntem yanlı sonuçlar verebilmektedir. Bu nedenle, nadir olay verileri için kullanılabilen üç farklı modelleme tekniği kullanıldı. En iyi model olan Firth Lojistik Regresyonu (FLR) sonuçlarına göre, rüzgâr hızı ve maksimum sıcaklık, 10 hektardan büyük orman yangınlarının oluşumunda istatistiksel olarak önemli değişkenler olarak bulundu.

Anahtar Kelimeler

• İklim Değişikliği
• Nem
• Doğal Tehlike
• Cezalandırılmış Regresyon

Kaynakça

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