Wildfire Modeling

Wildfire modeling aims to predict fire spread and behavior to improve prevention, mitigation, and response efforts. Current research heavily utilizes machine learning, particularly neural networks and cellular automata, often integrated with physics-based models and data assimilation techniques from satellite imagery to improve accuracy and address challenges posed by incomplete data. These advancements are crucial for enhancing wildfire forecasting, optimizing resource allocation (e.g., deploying firefighting assets), and ultimately reducing the devastating impacts of wildfires on ecosystems and communities. The development of large, publicly available datasets is also a key focus to support the training and validation of these increasingly sophisticated models.