A single band TIR-based algorithm to detect low-to-high thermal anomalies in volcanic regions

Volcanic eruptions pose a major threat to at least 800 million people. Studies revealed that ~50% of the ~1400 potentially active subaerial volcanoes still lack conventional ground-based monitoring networks. In this context, satellite data proves to be a cost-effective, yet reliable, information source for detecting early signs of volcanic activity and monitoring the evolution of eruptive events.
Within the past two decades, several moderate resolution (~1 km) Mid-InfraRed (MIR) satellite-based volcano monitoring systems have been developed, mostly targeting high-temperature anomalies associated with eruptive activity. Subtle thermal anomalies, however, might occur from years to days prior major volcanic unrests and/or eruptions, and persist for a long time during the cooling stage of the erupted deposits.
Studies revealed that Thermal InfraRed (TIR) bands, often characterised by higher spatial resolution (< 100 m) but lower revisit time (> 6 days), are well suited to detect subtle thermal anomalies. Yet, even in a high-temperature domain, TIR observations typically prove more effective in accurately determining the dimensions of active and cooling lava flows. Besides, high resolution TIR channels allow the retrieval of more detailed spatial information but with a temporal resolution inadequate for daily monitoring.
Forefront TIR-equipped platforms, however, like the Visible Infrared Imaging Radiometer Suite (VIIRS), offer an unprecedented trade-off between spatial (375 m) and temporal resolution (up to 4 acquisitions of the same target per day), having the potential to provide accurate heat flux measurements before, during and after an eruption. 
Here we present a single-band TIR-based algorithm capable of detecting thermal anomalies in a broad range of volcanic settings, from crater lakes and localised low-temperature hydrothermal systems to high-temperature effusive events. The algorithm – based on temporal and contextual analyses to identify thermally anomalous pixels – can detect thermal anomalies for pixel-integrated temperatures as low as 0.5 K above the surrounding hot-spot-free background and as far as 25 km from the volcano’s summit while maintaining a false positive rate of ~2%.
Results emerging from selected case studies envisage that the system will prove instrumental for detecting early signs of volcanic activity and for monitoring the evolution of thermal emissions, from unrest to eruption. Furthermore, the compilation of statistically robust multidecadal thermal datasets will provide novel insights and new perspectives into volcano monitoring, laying the ground for forthcoming higher-resolution TIR missions.