Prediction of Turkey Forest Fire using Random Forest Regressor

Forest fire is one of critical challenge for the survival of human, animal, and environment. Turkey is a particularly dangerous location for forest fires. Over the past two decades, there have been over 2,000 forest fires annually, each of which has caused at least one fatality.48^% of them are due to the actions of people. When the rates of fires with unknown causes are factored in, this number jumps up to 71%. Based on the satellite data, this investigation has been carried out in turkey, comprising 39,289 forest fire data rows and 13 columns. This exhaustive study, which is based on the data points spanning the years 2000–2020 and seeks to predict forest fires, is the result of extensive research. The method of machine learning known as “Random Forest” serves as the foundation for the predictive model. According to the results of the experiments, the Random Forest Regressor performs better than other models in terms of accuracy rate, MAE, and RMSE value in pairs of 89.450/0,3.42460,6.198039 subsequently. This study will be of tremendous value to the Turkish government as well as the citizens, and it is expected to have an impact on the following permitting individuals to take safeguards against possible forest fires and get themselves ready for them should they occur. However, there is still an opportunity for development and improvisation in the situation with information.