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Open AccessArticle

Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS–MIROVA Thermal Data Series

1
Dipartimento di Scienze della Terra, Università di Torino, V. Valperga Caluso 35, 10125 Torino, Italy
2
Dipartimento di Scienze della Terra, Università di Firenze, V. G. La Pira 4, 50121 Firenze, Italy
3
NATRISK: Centro Interdipartimentale sui Rischi Naturali in Ambiente Montano e Collinare, Università di Torino, Largo Paolo Braccini, 2, 10095 Grugliasco (TO), Italy
4
Dep. Computer Vision & Remote Sensing, Technische Universität Berlin, 10587 Berlin, Germany
5
GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(5), 820; https://doi.org/10.3390/rs12050820
Received: 9 January 2020 / Revised: 25 February 2020 / Accepted: 1 March 2020 / Published: 3 March 2020
(This article belongs to the Special Issue Satellite Remote Sensing of High-Temperature Thermal Anomalies)
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. View Full-Text
Keywords: SENTINEL-2; volcanic hot-spot detection; thermal anomalies; high-spatial resolution; volcanic activity; MODIS; MIROVA SENTINEL-2; volcanic hot-spot detection; thermal anomalies; high-spatial resolution; volcanic activity; MODIS; MIROVA
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MDPI and ACS Style

Massimetti, F.; Coppola, D.; Laiolo, M.; Valade, S.; Cigolini, C.; Ripepe, M. Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS–MIROVA Thermal Data Series. Remote Sens. 2020, 12, 820.

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