Research and applications on wildfire forecasting and management have become increasingly critical due to escalating climate change and variability. Wildfires pose severe threats to communities, economies, and ecosystems, resulting in extensive damage and presenting hard challenges for disaster response and resource management. Advanced tools and techniques are essential to improve our ability to predict, mitigate, and manage wildfire risks effectively. However, applications in wildfire forecasting often lack good training datasets, and artificial intelligence can be limited by the lack of interpretability. This session solicits applications of artificial intelligence to address the multi-disciplinary challenges in wildfire forecasting and management. Topics could include, but are not limited to, real-time wildfire forecasting and early warning systems, ignition modelling, monitoring and supression strategies, post-fire impact analysis and recovery, monitoring and sensor integration, etc.

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