3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide
Jan Blahůt
1
Institute of Rock Structure and Mechanics, The Czech Academy of Sciences, V Holešovičkách 94/41, 18200 Prague, Czechia
2
Research Institute of Geodesy, Topography and Cartography, Ústecká 98, 25066 Zdiby, Czechia
3
Centro Geofísico de Canarias, Instituto Geográfico Nacional, Calle la Marina 20, 38001 Santa Cruz de Tenerife, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(16), 5469; https://doi.org/10.3390/app10165469
Received: 30 June 2020 / Revised: 28 July 2020 / Accepted: 3 August 2020 / Published: 7 August 2020
(This article belongs to the Special Issue Novel Approaches in Landslide Monitoring and Data Analysis)
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 Andrés 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.
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Keywords:
slow-moving landslide; landslide monitoring; time-series analysis; San Andrés Landslide; El Hierro; Canary Islands
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MDPI and ACS Style
Blahůt, J.; Balek, J.; Eliaš, M.; Meletlidis, S. 3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide. Appl. Sci. 2020, 10, 5469.
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