Abstract
In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new hot-spot detection algorithm developed for SENTINEL-2/MSI data that combines spectral indices on the SWIR bands 8a-11-12 (with a 20-meter resolution) with a spatial and statistical analysis on clusters of alerted pixels. The algorithm is able to detect hot-spot-contaminated pixels (S2Pix) in a wide range of environments and for several types of volcanic activities, showing high accuracy performances of about 1% and 94% in averaged omission and commission rates, respectively, underlining a strong reliability on a global scale. The S2-derived thermal trends, retrieved at eight key-case volcanoes, are then compared with the Volcanic Radiative Power (VRP) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and processed by the MIROVA (Middle InfraRed Observation of Volcanic Activity) system during an almost four-year-long period, January 2016 to October 2019. The presented data indicate an overall excellent correlation between the two thermal signals, enhancing the higher sensitivity of SENTINEL-2 to detect subtle, low-temperature thermal signals. Moreover, for each case we explore the specific relationship between S2Pix and VRP showing how different volcanic processes (i.e., lava flows, domes, lakes and open-vent activity) produce a distinct pattern in terms of size and intensity of the thermal anomaly. These promising results indicate how the algorithm here presented could be applicable for volcanic monitoring purposes and integrated into operational systems. Moreover, the combination of high-resolution (S2/MSI) and moderate-resolution (MODIS) thermal timeseries constitutes a breakthrough for future multi-sensor hot-spot detection systems, with increased monitoring capabilities that are useful for communities which interact with active volcanoes.
Highlights
Satellite thermal remote sensing is a key discipline to study and monitor recent and ongoing volcanic activity
The concurrence of both spatial and statistical filters (Step 3 in the algorithm) allowed to exclude hot-spot pixels not directly related to the volcanic hot spot or triggered by instrument optics effects combined to intense thermal emissions
This enhancement is extremely relevant for monitoring purposes, for automated system applications, since pixels affected by halo effects might have been wrongly interpreted as hot materials emplacing outside the summit crater terrace of Stromboli or the Yasur crater rim, with relevant implications for hazard assessment
Summary
Satellite thermal remote sensing is a key discipline to study and monitor recent and ongoing volcanic activity. Thermal signals from volcanoes can be investigated by using new sensors and processing algorithms, and such advancements will continue to make thermal remote sensing an expanding field, whose techniques represent a safe and low-cost tool for improving volcano comprehension [18]. Fundamental parameters, such as the location, size and temperature of the hot target(s), the radiant flux and the time-averaged lava discharge rates (TADR) can be estimated from IR remote sensing and delivered to research centers, observatories and protection agencies that are in charge of volcano monitoring [19,20]. The prompt interpretation of the thermal signature is a challenge, for volcano monitoring and real-time assessment of hazardous scenarios
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