<p>In the satellite thermal remote sensing, the high-spatial resolution sensors may improve thermal constraining of volcanic phenomena, with direct implications on the comprehension of volcanic processes and monitoring purposes. Here we present a new hot-spot detection algorithm, developed for SENTINEL 2 (S2) data, which combines contextual spectral and spatial analysis, applied on the 8a-11-12 SWIR bands with 20 meters/pixel resolution. The algorithm is able to detect and count the number of hotspot-contaminated pixels (S2Pix), in a wide range of environments and for several types of volcanic activities. The S2-derived thermal trends, retrieved at different worldwide key-cases volcanoes, are than compared with the Volcanic Radiative Power (VRP) from MODIS images processed by the MIROVA system during the period 2016-2019. Dataseries showed an overall excellent correlation between the two imagery suites, enhancing the higher sensitivity of SENTINEL-2 to detect small size and subtle, low-temperature thermal signals. Results outline a relation between the S2Pix and VRP ratios and the volcanic processes (i.e. lava flows, domes, lakes, open-vent activity) producing a distinct pattern in terms of size and intensity of the thermal anomaly. Moreover, the high-spatial resolution of S2 imagery potentiality let to decrypt which is the thermal contribution of the different active volcanic portions, and to understand their evolution in terms of intensity and persistence. Our analysis indicates how the combination of high- (S2) and moderate- (MODIS) resolution thermal timeseries represent an improvement in the space-based volcano monitoring that can be useful for monitoring applications and communities which relate with active volcanoes.</p>
Rapid biodiagnostic ex vivo imaging at 1 μm pixel resolution with thermal source FTIR FPA