A Comparative Study of the Forest Fire Danger Index Calculation Methods Using Backpropagation

Abstract

Forest fires are one of the threats of disasters in Indonesia. Rising earth temperatures add to the higher potential contribution of forest fires. Many forest fire hazard index calculation methods have been developed to analyze the impact categories arising from changes in meteorological parameters. Each calculation method has advantages in calculating the magnitude of the potential. One method of calculating the forest fire hazard index is needed from many choices of methods that have the highest level of accuracy to predict the potential for a fire. A comparative study of the methods will be validated and guide the best calculating procedure to be implemented for the prediction. Predictions that have excellent accuracy and precision can be used as an early warning system. This study will predict forest fires for each calculation method using the Backpropagation algorithm, then analyze the accuracy of the prediction results using Relative Operating Characteristics (ROC). The methods compared include the methods that have been used in Indonesia as a country that has tropical rainforests, namely Keetch-Byram Drought Index (KBDI), Standard Precipitation Index (SPI), McArthur Forest Fire Danger Index (MFFDI), and Fire Weather Index (FWI). Through a comparative study of this calculation model, it is concluded that MFFDI is the best method of calculating the fire hazard index with an accuracy value of 0.917 and a precision value of 0.667.

Forest Fuel Drying, Pyrolysis and Ignition Processes during Forest Fire: A Review

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Legal Dynamics in Environmental Accountability: A Case Study of Forest Fire Litigation in Indonesia

“…However, despite their importance, forest fires annually devastate millions of hectares of forest [2]. Hadisuwito and Hassan [3] assert that forest fires pose a severe threat during the dry season, particularly in tropical forest regions like Indonesia. Consequently, the impact of these fires is considerable, as highlighted by Gnusov et al [2].…”

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Projections of wildfire risk and activities under 1.5 °C and 2.0 °C global warming scenarios

“…Among them, the FFDI is very useful in predicting and assessing forest fire risk and has been applied successfully in operations in Australia [40,41], Amazonia, and other tropical areas [42,43]. Hadisuwito and Hassan [44] suggested that the FFDI is a better compound fire hazard index with a higher level of accuracy and precision than the KBDI and FWI in Indonesia. Some studies have also used it to estimate wildfire risk on a global scale [45,46].…”