Monitoring underwater hydrothermal degassing at Baia di Levante (Vulcano Island) using high‑resolution and hyperspectral satellite data

Vulcano island, located in the Italian Eolian Archipelago, is an active hydrothermal volcanic system that last erupted in 1888-1890. Since then, activity has persisted at fumaroles, thermal ground and soil degassing at the Fossa crater, and also at the Baia di Levante (Levante Bay). The bay hosts a secondary geothermal system fed by a shallow hydrothermal aquifer that is heated by magmatic gases resulting in coastal/offshore low temperature fumaroles and soil CO₂ degassing in the Acqua Calde beach. In 2021, Vulcano island entered a new phase of unrest marked by increased degassing, seismicity, heat release and deformation at the Fossa cone, followed by increased diffuse soil degassing at the Vulcano Porto area that prompted protective measures for residents. In May 2022, gas output at the Baia di Levante area rose significantly, coinciding with the first observed sea whitening event. This area, one of the main tourist attractions of the island, now faces heightened hazard from degassing and potential explosive activity. Other studies reported elevated CO₂ and H₂S fluxes (diffuse and convective), anomalous seawater pH, and extremely high dissolved CO₂ concentrations, even in zones with limited visible hydrothermal activity. Since 2022, multiple sea whitening events were recorded, though their variable duration prevents construction of a continuous timeline from punctual surveys. For this study, we used the archives of three high spatial resolution sensors – Terra’s Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat 8 and 9 Operational Land Imager (OLI) and Sentinel-2 Multispectral instrument (MSI) – to detect and quantify the extent and intensity of these events. The sea anomalies are compared to the ground-based measurements of degassing and heat release, as well as thermal anomalies identified by the ASTAD machine learning algorithm, a convolutional neural network (CNN)-based model designed specifically for ASTER data. Preliminary work has detected thermal anomalies during three episodes in 2022, 2023 and 2025. The second phase of the study is using hyperspectral PRecursore IperSpettrale della Missione Applicativa (PRISMA) data to test whether geochemical species in the precipitates (e.g., carbonates, sulphates) can be identified and quantified. This work will provide new insights into the coupling between degassing, seawater chemistry, and volcanic hazards at Vulcano and ultimately is applicable globally with these orbital sensors.