SSTAR (Subtle Surface Thermal Anomalies Recognizer) is a satellite-based analysis framework designed to detect and monitor diffuse, low-amplitude thermal anomalies associated with volcanic and hydrothermal activity. Unlike conventional approaches that focus on high-temperature hotspots (e.g., lava flows, fumaroles, active vents), SSTAR is specifically tailored to identify subtle, spatially distributed thermal signals that may precede or accompany subsurface unrest.
The method is based on the analysis of long-term thermal infrared satellite data, where temperature variations within a region of interest are evaluated relative to a carefully selected reference area. This relative approach, combined with robust cloud filtering, uncertainty estimation, and temporal smoothing, allows SSTAR to isolate weak thermal signals from environmental noise and seasonal variability.
SSTAR is implemented as a transparent and reproducible workflow, enabling both researchers and monitoring agencies to analyze thermal time series in a consistent manner. The platform presented here provides near-real-time updates of SSTAR results for selected volcanoes, supporting the interpretation of ongoing activity and contributing to hazard assessment.
SSTAR can be downloaded from: XXXXX
For more details, please refer to the following reference:
Girona, T., L. Brenot (2026), SSTAR: A user-friendly framework for detecting and monitoring subtle thermal precursors to volcanic eruptions — application to Shishaldin, Alaska. Earth, Planets and Space. (In review).