3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985891%3A_____%2F20%3A00532904" target="_blank" >RIV/67985891:_____/20:00532904 - isvavai.cz</a>
Alternative codes found
RIV/00025615:_____/20:N0000039
Result on the web
<a href="https://www.mdpi.com/2076-3417/10/16/5469" target="_blank" >https://www.mdpi.com/2076-3417/10/16/5469</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app10165469" target="_blank" >10.3390/app10165469</a>
Alternative languages
Result language
angličtina
Original language name
3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10505 - Geology
Result continuities
Project
<a href="/en/project/GJ16-12227Y" target="_blank" >GJ16-12227Y: El Hierro megalandslide dynamics analysed using “big data” to predict the future behaviour of megalandslides on other volcanic islands</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Sciences-Basel
ISSN
2076-3417
e-ISSN
—
Volume of the periodical
10
Issue of the periodical within the volume
16
Country of publishing house
CH - SWITZERLAND
Number of pages
16
Pages from-to
5469
UT code for WoS article
000564874700001
EID of the result in the Scopus database
2-s2.0-85089898509