Evidence map›Paper›PMID 37330531›Full record

ArticleScientific reports2023

Tracking volcanic explosions using Shannon entropy at Volcán de Colima.

Pablo Rey-Devesa, Janire Prudencio, Carmen Benítez, Mauricio Bretón, Imelda Plasencia, Zoraida León, Félix Ortigosa, Ligdamis Gutiérrez, Raúl Arámbula-Mendoza, Jesús M Ibáñez

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In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Pablo Rey-DevesaDepartment of Theoretical Physics and Cosmos, Science Faculty, University of Granada, Avd. Fuentenueva s/n, 18071, Granada, Spain. pablord@ugr.es.
Janire PrudencioDepartment of Theoretical Physics and Cosmos, Science Faculty, University of Granada, Avd. Fuentenueva s/n, 18071, Granada, Spain.
Carmen BenítezDepartment of Signal Theory, Telematics and Communication, Informatics and Telecommunication School, University of Granada, 18071, Granada, Spain.
Mauricio BretónCentro Universitario de Estudios Vulcanológicos (CUEV), Observatorio Vulcanológico, Universidad de Colima, Colima, Mexico.
Imelda PlasenciaCentro Universitario de Estudios Vulcanológicos (CUEV), Observatorio Vulcanológico, Universidad de Colima, Colima, Mexico.
Zoraida LeónCentro Universitario de Estudios Vulcanológicos (CUEV), Observatorio Vulcanológico, Universidad de Colima, Colima, Mexico.
Félix OrtigosaCentro Universitario de Estudios Vulcanológicos (CUEV), Observatorio Vulcanológico, Universidad de Colima, Colima, Mexico.
Ligdamis GutiérrezDepartment of Theoretical Physics and Cosmos, Science Faculty, University of Granada, Avd. Fuentenueva s/n, 18071, Granada, Spain.
Raúl Arámbula-MendozaCentro Universitario de Estudios Vulcanológicos (CUEV), Observatorio Vulcanológico, Universidad de Colima, Colima, Mexico.
Jesús M IbáñezDepartment of Theoretical Physics and Cosmos, Science Faculty, University of Granada, Avd. Fuentenueva s/n, 18071, Granada, Spain.

Funding

Ministerio de Ciencia e Innovación PID2019-106260GB-I00
6 · The paper itself

Abstract

The main objective of this work is to show that Shannon Entropy (SE) calculated on continuous seismic signals can be used in a volcanic eruption monitoring system. We analysed three years of volcanic activity of Volcán de Colima, México, recorded between January 2015 and May 2017. This period includes two large explosions, with pyroclastic and lava flows, and intense activity of less energetic explosion, culminating with a period of quiescence. In order to confirm the success of our results, we used images of the Visual Monitoring system of Colima Volcano Observatory. Another of the objectives of this work is to show how the decrease in SE values can be used to track minor explosive activity, helping Machine Learning algorithms to work more efficiently in the complex problem of distinguishing the explosion signals in the seismograms. We show that the two big eruptions selected were forecasted successfully (6 and 2 days respectively) using the decay of SE. We conclude that SE could be used as a complementary tool in seismic volcano monitoring, showing its successful behaviour prior to energetic eruptions, giving time enough to alert the population and prepare for the consequences of an imminent and well predicted moment of the eruption.

Indexed as

DisastersExplosionsEnvironmentForecastingVolcanic Eruptions

Identifiers

PMID37330531
PMCPMC10276871

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.