ForestFireAI: Large-scale Prediction of Forest Fire Drivers from Space Using Multi-source Remote Sensing Data and Artificial Intelligence Techniques

With the increasing frequency and intensity of forest fires, it is essential to better understand the drivers causing them.

Identifying forest fire drivers offer valuable insights that can enhance our comprehension of forest fire variability and guide targeted regional risk management strategies.

Recent advancements in satellite remote sensing and machine learning data processing techniques have significantly improved fire monitoring.

However, while these efforts have resulted in accurate fire maps, they do not provide information about the underlying causes.

Consequently, the full potential of Earth Observation data, along with advanced data processing and modelling techniques for studying the forest fire drivers, remains largely unexplored.

The ForestFireAI project aims to leverage the availability of multi-source and multi-temporal Earth Observation data to propose new AI algorithms for estimating forest fire drivers.

This includes creating a benchmark dataset of forest fire drivers in Europe, which will serve as a ground truth data for evaluating developed advanced AI algorithms.

Moreover, the project will focus on developing AI techniques to improve the spatial resolution of data, use multi-source data and their temporal resolution, and establish efficient processing schemes for detecting forest fire drivers, such as human activities, high temperature, fuel, and dryness.

To ensure the reliability, efficiency, and scalability of the developed algorithms, uncertainty-aware, explainable, and hybrid physical/data-driven techniques will be incorporated.

Through this multidisciplinary approach—bringing together expertise in remote sensing, computer science, and forest ecology—ForestFireAI will take important steps toward developing the algorithms necessary for better understanding forest fire drivers.

This knowledge could contribute in reducing the risk of extreme forest fires and will accelerate the advancement of Dr Benyamin Hosseiny’s research.