Forest Wildfire Observation

Forest wildfire observation research focuses on developing accurate and timely detection and prediction methods to mitigate the devastating impacts of wildfires. Current efforts leverage diverse remote sensing data (satellite imagery, thermal data) and advanced machine learning techniques, including deep learning models (e.g., convolutional neural networks, physics-informed neural networks), and classical algorithms (e.g., decision trees, random forests) to improve hotspot detection, burn severity mapping, and wildfire risk prediction. These advancements are crucial for enhancing wildfire management strategies, improving resource allocation, and ultimately reducing the ecological and economic losses associated with these increasingly frequent and severe events.