remote sensing Article Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS–MIROVA Thermal Data Series Francesco Massimetti 1,2,*, Diego Coppola 1,3 , Marco Laiolo 1,3 , Sébastien Valade 4,5, Corrado Cigolini 1,3 and Maurizio Ripepe 2 1 Dipartimento di Scienze della Terra, Università di Torino, V. Valperga Caluso 35, 10125 Torino, Italy;
[email protected] (D.C.);
[email protected] (M.L.);
[email protected] (C.C.) 2 Dipartimento di Scienze della Terra, Università di Firenze, V. G. La Pira 4, 50121 Firenze, Italy; maurizio.ripepe@unifi.it 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;
[email protected] 5 GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany * Correspondence:
[email protected] Received: 9 January 2020; Accepted: 1 March 2020; Published: 3 March 2020 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.