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Abstract text
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On 20 December 2020, after about two years of quiescence, a new eruption started at Kīlauea volcano (Hawaiʻi, USA) by three fissures opening on the inner walls of Halema`uma`u Crater. During the eruption, which produced lava fountains up to 50 m height, the lava cascaded into the summit water lake, generating a vigorous steam plume and forming a new lava lake at the base of the crater. In this study, we investigate the Kīlauea’s lava lake through the Normalized Hot Spot Indices (NHI) tool. The latter is a Google Earth Engine (GEE) App, which exploits mid-high spatial resolution daytime satellite data, from the Operational Land Imager (OLI) onboard of Landsat-8 and the Multispectral Instrument (MSI) onboard of Sentinel-2 to map thermal anomalies at global scale by satellite. In addition, offline processing of Landsat-8 nighttime data was performed. Results show that especially at daytime the NHI tool provided detailed information about the lava lake and relative space-time variations. Moreover, the hot spot area well approximated the area covered by the lava lake from U.S. Geological Survey (USGS) measurements when only the hottest NHI pixels were considered. By correcting Sentinel-2 MSI and Landsat-8 OLI daytime data for the influence of the solar irradiation, we estimated values of the radiant flux in the range 1-5 GW from hottest pixels during the period December 2020 to February 2021. Those values were about 1.7 times higher than Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) estimations, while the temporal trend of the radiant flux was comparable. Analysis of Landsat-8 OLI nighttime data showed a similar temporal trend of the radiant flux as observations from MODIS and VIIRS, but with a higher deviation compared to the daytime data. This study demonstrates that the NHI tool may provide a relevant contribution to investigate volcanic thermal anomalies also in well-monitored areas such as Kilauea, opening some challenging scenarios about their quantitative characterization also through its automated module performing operationally.
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