Clustering of eruptive events from high-precision strain signals recorded during the 2020–2022 lava fountains at the Etna volcano (Italy)

Abstract k -means algorithm applied on the strain signal. A novel procedure was developed to ensure a high-quality clustering process and obtain robust results. The analysis identified four groups of strain variations which stand out for their amplitude, duration and time derivative of the signal. The temporal distribution of the clusters highlighted a transition in different types of eruptions, thus revealing the importance of clustering the strain variations for monitoring the volcano activity and evaluating the associated hazards.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Clustering of eruptive events from high-precision strain signals recorded during the 2020–2022 lava fountains at the Etna volcano (Italy) ; volume:23 ; number:5 ; year:2023 ; pages:1743-1754 ; extent:12 ; Natural hazards and earth system sciences ; 23, Heft 5 (2023), 1743-1754 (gesamt 12)

Contributors, Places and Time

• Creator: Carleo, Luigi ; Currenti, Gilda ; Bonaccorso, Alessandro

Further information

• DOI: 10.5194/nhess-23-1743-2023
• URN: urn:nbn:de:101:1-2023051804325002095605
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 14.08.2025, 11:04 AM CEST