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3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide
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SYSNO ASEP 0532904 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title 3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide Author(s) Blahůt, Jan (USMH-B) RID, ORCID, SAI
Balek, Jan (USMH-B) ORCID
Eliaš, M. (CZ)
Meletlidis, S. (ES)Article number 5469 Source Title Applied Sciences-Basel. - : MDPI
Roč. 10, č. 16 (2020)Number of pages 16 s. Language eng - English Country CH - Switzerland Keywords slow-moving landslide ; landslide monitoring ; time-series analysis ; San Andrés Landslide ; El Hierro ; Canary Islands Subject RIV DB - Geology ; Mineralogy OECD category Geology R&D Projects GJ16-12227Y GA ČR - Czech Science Foundation (CSF) Method of publishing Open access Institutional support USMH-B - RVO:67985891 UT WOS 000564874700001 EID SCOPUS 85089898509 DOI 10.3390/app10165469 Annotation Featured Application Analysis of monitoring data from very slow-moving landslides. This paper presents a methodological approach to the time-series analysis of movement monitoring data of a large slow-moving landslide. It combines different methods of data manipulation to decrease the subjectivity of a researcher and provides a fully quantitative approach for analyzing large amounts of data. The methodology was applied to 3D dilatometric data acquired from the giant San Andres Landslide on El Hierro in the Canary Islands in the period from October 2013 to April 2019. The landslide is a creeping volcanic flank collapse showing a decrease of speed of movement during the monitoring period. Despite the fact that clear and unambiguous geological interpretations cannot be made, the analysis is capable of showing correlations of the changes of the movement with increased seismicity and, to some point, with precipitation. We consider this methodology being the first step in automatizing and increasing the objectivity of analysis of slow-moving landslide monitoring data. Workplace Institute of Rock Structure and Mechanics Contact Iva Švihálková, svihalkova@irsm.cas.cz, Tel.: 266 009 216 Year of Publishing 2021 Electronic address https://www.mdpi.com/2076-3417/10/16/5469
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