On December 20, 2020, a new eruption started at Kilauea volcano (Hawai'i, USA). During the eruption, 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 lava lake through the Normalized Hot Spot Indices (NHI) algorithm. The latter runs operationally within a Google Earth Engine (GEE) App (NHI tool), using Operational Land Imager (OLI) and Multispectral Instrument (MSI) data, to map volcanic thermal anomalies at global scale. Results show that the used algorithm provided information about the lava lake and relative space-time variations in agreement with field observations. By correcting 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. This study opens some challenging scenarios about the quantitative characterization of volcanic thermal features through the NHI tool.

Mapping and characterizing the Kilauea (Hawai'i) lava lake through Sentinel-2 MSI and Landsat-8 OLI observations of December 2020-February 2021

Genzano, N
;
Falconieri, A;Pergola, N;
2022-01-01

Abstract

On December 20, 2020, a new eruption started at Kilauea volcano (Hawai'i, USA). During the eruption, 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 lava lake through the Normalized Hot Spot Indices (NHI) algorithm. The latter runs operationally within a Google Earth Engine (GEE) App (NHI tool), using Operational Land Imager (OLI) and Multispectral Instrument (MSI) data, to map volcanic thermal anomalies at global scale. Results show that the used algorithm provided information about the lava lake and relative space-time variations in agreement with field observations. By correcting 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. This study opens some challenging scenarios about the quantitative characterization of volcanic thermal features through the NHI tool.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/156886
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