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SSTAR: A user-friendly application to track subtle thermal anomalies at volcanoes

Társilo Girona 1, Laure Brenot2

  • Affiliations: 1Alaska Volcano Observatory, Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA. 2G-Time, Université Libre de Bruxelles, Brussels, Belgium. 

  • Presentation type: Poster

  • Presentation time: Monday 16:30 - 18:30, Room Poster Hall

  • Poster Board Number: 151

  • Programme No: 3.1.43

  • Theme 3 > Session 1

Abstract

The past decades have been transformative for thermal monitoring of volcanoes, driven by the launch of new satellites and advancements in spectroscopic surface analysis instruments. These innovations have unveiled diverse thermal responses of volcanic surfaces to subsurface processes, revealing that many eruptions are preceded by various types of thermal anomalies. This underscores the importance of developing new methods to track these anomalies, leveraging existing data and maximizing the potential of current instruments in orbit. To address this need, we introduce SSTAR: Subtle Surface Thermal Anomalies Recognizer, a user-friendly application that analyzes subtle thermal unrest (~1 K) across large areas (several km2) using MODIS satellite data. Building upon the statistical thermal anomaly detection method of Girona et al. (2021), SSTAR analyzes pixel data to track the evolution of thermal anomalies at specific sites and map their spatiotemporal distribution over extensive regions. SSTAR offers several key features, including distinct filtering capabilities for identifying both long-term (years) and short-term (weeks) anomalies with uncertainty quantification using bootstrapping and Monte Carlo approaches. This application provides an interactive interface for seamless data analysis and is standalone, with the added flexibility for Matlab users to customize the scripts to meet specialized needs. We envision SSTAR as a valuable resource for students and researchers investigating subtle thermal anomalies at active volcanoes. Additionally, an upcoming version of SSTAR will support near real-time tracking of subtle thermal unrest, positioning it as a forward-looking tool to advance thermal monitoring of volcanoes in the decades ahead.