Forest Fire Simulation using Cellular Automata

The cellular automata model is a widely used method for simulating complex systems. Forest fire simulation represents one significant research direction within this framework. In this model, each forest unit is treated as a cellular automaton that can exist in one of three states: burning, unburned (healthy), or burned-out. The simulation typically implements transition rules where burning cells can ignite neighboring unburned cells based on probabilistic factors like wind direction and vegetation density. Through configuring different initial conditions and parameters such as ignition probability, spread rate, and forest density, various forest fire scenarios can be simulated to predict potential fire progression patterns. The model's implementation often utilizes matrix operations for state updates and visualization libraries for dynamic display. This simulation approach provides valuable insights into fire behavior, offering critical references for forest fire prevention strategies and emergency response planning. Key algorithmic considerations include neighborhood connectivity (Moore or von Neumann neighborhoods), time-step iterations, and state transition logic that determines how fires propagate through the cellular grid.