Automatic detection of volcanic ash clouds using MSG-SEVIRI satellite data and machine learning techniques

Torrisi, F. (2022) Automatic detection of volcanic ash clouds using MSG-SEVIRI satellite data and machine learning techniques. Il nuovo cimento C, 45 (4). pp. 1-10. ISSN 1826-9885

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Abstract

Volcanic ash emissions can pose serious hazard to population living at the edge of an active volcano and can cause widespread disruption to aviation operations. Here an innovative machine learning (ML) approach, developed in Google Earth Engine (GEE), is proposed to detect volcanic ash clouds. It exploits the MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager) images in the Thermal Infrared (TIR) range. This ML procedure was applied to the sequence of paroxysmal explosive events occurred at Mt. Etna between February and March 2021. It was demonstrated that machine learning algorithms combined with high temporal resolution satellite data offer a good solution to automatically detect, track and map a volcanic ash cloud.

Item Type:	Article
Subjects:	500 Scienze naturali e Matematica > 530 Fisica
Depositing User:	Marina Spanti
Date Deposited:	06 Sep 2022 11:36
Last Modified:	06 Sep 2022 11:36
URI:	http://eprints.bice.rm.cnr.it/id/eprint/21990

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