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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

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

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advancing Culture of Living with Landslides

ISBN

978-3-319-53486-2

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

333-340

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Ljubljana

Datum konání akce

29. 5. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000438667600038