3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/00025615:_____/20:N0000039

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

3D Dilatometer Time-Series Analysis for a Better Understanding of the Dynamics of a Giant Slow-Moving Landslide

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10505 - Geology

Projekt

<a href="/cs/project/GJ16-12227Y" target="_blank" >GJ16-12227Y: Dynamika megasesuvu na El Hierru analyzovaná pomocí "big data" za účelem predikce budoucího chování megasesuvů i na dalších vulkanických ostrovech</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Applied Sciences-Basel

ISSN

2076-3417

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

16

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

16

Strana od-do

5469

Kód UT WoS článku

000564874700001

EID výsledku v databázi Scopus

2-s2.0-85089898509