Monitoring giant landslide detachment planes in the era of big data analytics

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985891%3A_____%2F17%3A00481928" target="_blank" >RIV/67985891:_____/17:00481928 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-53487-9_38" target="_blank" >http://dx.doi.org/10.1007/978-3-319-53487-9_38</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-53487-9_38" target="_blank" >10.1007/978-3-319-53487-9_38</a>

Result language

angličtina

Original language name

Monitoring giant landslide detachment planes in the era of big data analytics

Original language description

A small mesh of sensors which monitor movements across detachment planes of the giant San Andrés Landslide on the northeastern lobe of El Hierro in the Canary Islands was established in 2013. In this paper we present the results obtained over a two year period spanning from October 2013 to October 2015. Our results demonstrate that the detachment planes are affected by sinistral strike slip displacements and subsidence of the depleted mass of the landslide. While these general trends are consistent the movements recorded at particular monitoring points differ in detail as one site is characterised by progressive strike slip and dip slip trends while another is characterised by movement pulses and reversals in the sense of movement. These findings contrast markedly with suggestions that the giant landslide is inactive and demonstrate that its reactivation is a possibility which cannot be dismissed categorically. Big data analytics have been used to identify interdependence between the recorded movements and a range of climatic and geophysical variables such as seismic data, tidal data, and geomagnetic data. We have found that the recorded movements correlate only weakly or moderately with climatic and seismic parameters but strongly to the horizontal and vertical intensity of the magnetic field. These findings are rather unexpected and we emphasise that special care must be taken in pushing the conclusions of a purely numerical analysis. The advantages of adopting a big data mindset led us to make significant improvements to the instrumental infrastructure in early 2016. These incremental improvements to the small mesh of sensors are driven partly by our desire to understand the kinematic behaviour of landslide itself and partly by our desire to explore the potential of big data analytics in geoscientific research.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10505 - Geology

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

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

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

Article name in the collection

Advancing Culture of Living with Landslides

ISBN

978-3-319-53486-2

ISSN

—

e-ISSN

—

Number of pages

8

Pages from-to

333-340

Publisher name

Springer

Place of publication

Cham

Event location

Ljubljana

Event date

May 29, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000438667600038