Emulation of Forest Fire Spread Using ResNet and Cellular Automata

Accurate quantitative simulation of forest fires is of great significance to the risk control of forest fires. Cellular automata model is often used to simulate forest fires. However, the traditional cellular automata model's cell state setting is too simple, and the conversion rules are not considered comprehensively enough, resulting in unsatisfactory simulation results. In this paper, it is proposed to learn the relationship between the burning state of cells and their own geographical conditions from the historical data of forest fires, and to convert the burning probability into the time required for complete burning of cells, so as to simulate different spreading speeds under different geographical conditions. Experiments show that this is a potentially effective method for forest fire simulation.