Advancing Wildfire Forecasting using Explainable AI

Wildfire events have been increasing globally due to climate change, which makes it essential to improve our ability to anticipate fire danger and understand the driving mechanisms on a global scale. The SeasFire project, funded by the European Space Agency (ESA), aims to address this challenge by enhancing global fire forecasting capabilities using Earth Observation data.
The National Observatory of Athens (NOA) collected and analyzed seasonal fire driver data, such as climate, vegetation, oceanic indices, and population density, along with burned areas data from 2001-2021. Initial studies have shown that Deep Learning can potentially improve short-term regional and long-term global wildfire forecasting. However, to better understand which climate variables are more critical for forecasting wildfire events in different lead times and eco regions, Explainable AI (XAI) techniques need to be leveraged.
The outcome of this challenge will improve our ability to predict wildfire events, enabling more effective responses and management of fire risk globally.