FOREST FIRE BEHAVIOR PREDICTION WITH MULTIVARIATE REGRESSION

Abstract

A forest fire starts on the surface of forest and is quite difficult to extinguish when it spreads the hill. Therefore, it is very important to extinguish a forest fire and estimate its behavior before it jumps to hill of trees. In this study, 151 data set was obtained from 21 controlled grassland fire, and then four different regression models were tested with this data and forest fire behavior was tried to model. Hence, weed, litter and humus layer samples were taken from forest floor, and then they were dried in the oven. Additionally, mobile weather station was established in the region, and every stage of fire was measured and recorded on camera. Later in the MATLAB environment, four different regression models were developed with fire data. In all of the models developed, it was used the burned area as the dependent variable and weed, litter, humus, temperature, dew point, relative humidity, wind speed and time as independent variable. One of these regression models that contains coefficients of independent variables multiplied together and its square was R2 with the value of 0.854 (p

Keywords

• Multivariate Regression Analysis, Fire Behavior Modeling, Fire Behavior Prediction, Fire Propagation Model, Regression Analysis,

ORMAN YANGIN DAVRANIŞININ ÇOK DEĞİŞKENLİ REGRESYONLA TAHMİN EDİLMESİ

Öz

Bir orman yangını örtüde başlar ve tepeye sıçradığında ise söndürmek oldukça zorlaşır. Bu yüzden çıkan bir orman yangınının tepeye sıçramadan söndürülmesi ve yangın davranışının tahmin edilmesi oldukça önemlidir. Bu çalışmada ise çıkartılan 21 kontrollü örtü yangınından elde edilen 151 veri seti, dört farklı regresyon modeliyle denenip, orman yangın davranışı modellenmeye çalışılmıştır. Bunun için orman yüzeyindeki bulunan diri örtü, ölü örtü ve humus katmanlarından örnekler alınmış ve bu örnekler fırında kurutulmuştur. Bunun dışında yangın çıkartılacak bölgede mobil meteoroloji istasyonu kurulmuş ve yangının her aşaması ölçülüp, kamerayla kaydedilmiştir. Daha sonra matlab ortamında veriler üzerinde dört farklı regresyon modeli geliştirilmiştir. Geliştirilen modellerin tamamında bağımlı değişken olarak yanan alan, bağımsız değişken olarak ise diri örtü, ölü örtü, humus, sıcaklık, çiğ noktası, bağıl nem, rüzgar hızı ve zaman kullanılmıştır. Bu regresyon modellerinden bağımsız değişkenlerin katsayılarının birbiriyle çarpımını ve karelerini içeren eğri R2 0.854 (p

Anahtar Kelimeler

• Çok Değişkenli, Yangın Davranış Modelleme, Yangın Davranış Tahmini, Yangın Yayılım Modeli, Regresyon Analizi,

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