Wildfires pose a significant and growing threat to both human populations and the environment. Climate change exacerbates this risk by increasing the frequency, duration, and severity of wildfires. Rising temperatures, prolonged droughts, and shifting weather patterns create conditions more conducive to wildfire spread, expanding the range of vulnerable areas and turning wildfires into a complex global challenge.
The availability of high-resolution, geo-referenced digital data underscores the need for advanced tools to model wildfire dynamics. A critical task is transforming these vast datasets into actionable insights for stakeholders. Recent advancements in computational science, particularly in the development of innovative algorithms, are essential for understanding and addressing wildfire behaviour and vulnerability.
This session aims to bring together experts from geosciences, climatology, forestry and territorial planning to enhance our understanding of these critical fire-related dynamics and to explore innovative strategies for mitigation and resilience. By fostering interdisciplinary collaboration, we seek to advance the science of wildfire prediction, prevention, and post-fire recovery, ultimately contributing to more effective responses to the growing threat posed by wildfires in a changing climate.
We welcome contributions on topics such as:
• Methodologies for recognizing, modelling, and predicting wildfire spatio-temporal patterns.
• Pre- and post-fire assessments, including fire mapping, severity evaluations, and risk management.
• Long-term analysis of wildfire trends in relation to climate change and land use changes.
• Fire spread modelling and studies on fire-weather relationships.
• Post-fire vegetation recovery and phenology.
Join us in advancing the study of wildfires and developing strategies to mitigate their impact.
"Spatial and Temporal Dynamics of Wildfires: Models, Theory, and Reality.
Convener:
Marj Tonini
|
Co-conveners:
Andrea TrucchiaECSECS,
Francesca Di Giuseppe,
Marco Turco,
Shelby CorningECSECS