MACHINE LEARNING-BASED FOREST FIRE PREDICTION MODEL UTILIZING UAV VIDEOS

Abstract

ABSTRACT-Forest fires represent a pervasive and significant natural calamity, yearly devastating millions of hectares of forest and presenting a grave danger to human life and property. Precise quantitative forecasting of forest fire propagation is crucial for formulating prompt risk management plans and executing efficient firefighting methods. This work presents a Forest Fire Spread Behavior Prediction (FFSBP) model, which has two essential components: the Forest Fire Spread Process Prediction (FFSPP) model and the Forest Fire Spread Results Prediction (FSRP) model. The FFSPP model predicts the direction and velocity of forest fire propagation by integrating the Cellular Automata model with the Wang Zhengfei model.