The severity of wildfire damage increases due to dry weather and climate change around the world. While climate change is a contributing factor to the increasing incidence of wildfires, the consequences of these fires extend far beyond their initial outbreak. Wildfires not only contaminate soil, pollute groundwater, and saturate the atmosphere with harmful substances, but they also devastate ecosystems and release greenhouse gases, further exacerbating the long-term effects of global warming. There remain numerous challenges that we need to understand, such as these complex relationships and the nature of wildfires. To improve understanding of wildfire behavior, various sources can be utilized such as remote sensing, numerical models, and chemical transport model. These days, artificial intelligence is actively used in environmental science, and not only it shows better performance than traditional techniques in monitoring or forecasting, but it is also widely used to understand essential information or complex relationships between disasters.
Therefore, this session invites contributions providing new insights into wildfire behavior through satellite data and artificial intelligence. It includes any extended application for air quality or climate extremes related to wildfires. This session also welcomes case studies of large fire events. The expected topics for this session are listed, but not limited to that.
- Wildfire monitoring and forecasting
- Smoke and air quality modeling
- Carbon emission estimation
- Wildfire risk assessment
- Ecosystem recovery and rehabilitation
- Wildfire behavior analysis (e.g. fire spread)
- Climate change and wildfire trends