Wildfires pose a significant and growing threat to both human populations and the environment. Climate change exacerbates this risk by increasing their frequency, duration, and severity. Rising temperatures, prolonged droughts, and shifting weather patterns create increasingly favourable conditions for fire ignition and spread, expanding the range of vulnerable areas and making wildfires a complex global challenge.

The increasing availability of high-resolution, georeferenced data calls for advanced approaches to analyse and model wildfire dynamics. Remote sensing, geospatial analysis, artificial intelligence, and data-driven and numerical modelling offer new opportunities to transform large and heterogeneous datasets into actionable information for wildfire prediction, risk assessment, and management.

This session aims to bring together experts from geosciences, climatology, forestry, and territorial planning to improve our understanding of fire-related dynamics and explore innovative strategies for mitigation and resilience. By fostering interdisciplinary collaboration, we seek to advance wildfire prediction, prevention, and post-fire recovery, contributing to more effective responses to the growing threat posed by wildfires in a changing climate.

We welcome contributions on topics such as:
• Remote sensing, geospatial and computational methods for recognizing, modelling, and predicting wildfire spatio-temporal patterns.
• Pre- and post-fire assessments, including fire mapping, severity evaluation, and risk management.
• AI, machine learning, and data-driven approaches for wildfire analysis and prediction.
• Long-term analyses of wildfire trends in relation to climate and land-use changes.
• Fire spread modelling and fire-weather relationships.
• Post-fire vegetation recovery and phenology.

Join us in advancing wildfire research and developing innovative strategies to better understand and mitigate its impacts.