Exploring the potential of artificial intelligence in volcanic hazard monitoring from space.

Operational monitoring centers like the Etna Volcano Observatory (EVO) are nowadays heavily reliant on remote sensing data from a variety of optical and thermal sensors to provide time-critical hazard information. The huge amount of satellite data available requires new approaches capable of processing them automatically and artificial intelligence (AI) addresses these needs. Here, an AI-based platform was developed to monitor in near real-time the volcanic activity from space. AI algorithms are used to retrieve information about the ongoing volcanic activity. Under this perspective, a key role is played by Machine Learning since it overcomes the issues related to hard coded/explicit rules by implicitly learning them from historical satellite data. Volcanic eruptions are then fully characterized estimating the thermal energy release and quantifying the erupted products. This task is achieved by combining a variety of multispectral satellite datasets, ranging from visible to infrared and radar, with different spatial and temporal features. We explore the potential of this web-based satellite-data--driven platform during the recent eruptive events on Stromboli and Etna volcanoes.