Data Publication

Supplementary material to "Machine Learning can predict the timing and size of analog earthquakes"

Corbi, Fabio | Sandri, Laura | Bedford, Jonathan | Funiciello, Francesca | Brizzi, Silvia | Rosenau, Matthias | Lallemand, Serge

GFZ Data Services

(2018)

Descriptions

This data set includes the results of digital image correlation of one experiment on subduction megathrust earthquakes with interacting asperities performed at the Laboratory of Experimental Tectonics (LET) Univ. Roma Tre in the framework of AspSync, the Marie Curie project (grant agreement 658034) lead by F. Corbi in 2016-2017. Detailed descriptions of the experiments and monitoring techniques can be found in Corbi et al. (2017 and 2019) to which this data set is supplementary material. We here provide Digital Image Correlation (DIC) data relative to a 7 min long interval during which the experiment produces 40 seismic cycles with average duration of about 10.5 s (see Figure S1 in Corbi et al., 2019). The DIC analysis yields quantitative about the velocity field characterizing two consecutive frames, measured in this case at the model surface. For a detailed description of the experimental procedure, set-up and materials used, please refer to the article of Corbi et al. (2017) paragraph 2. This data set has been used for: a) studying the correlation between apparent slip-deficit maps and earthquake slip pattern (see Corbi et al., 2019; paragraph 4); and b) as input for the Machine Learning investigation (see Corbi et al., 2019; paragraph 5). Further technical information about the methods, data products and matlab scripts is proviced in the data description file. The list of files explains the file and folder structure of the data set.

Keywords


Originally assigned keywords
machine Learning
analogue models of geologic processes
subduction megathrust earthquakes
asperities
multi-scale laboratories
EPOS
Analog modelling results
Software tools
EARTH SCIENCE > SOLID EARTH > TECTONICS > PLATE TECTONICS > FAULT MOVEMENT
EARTH SCIENCE > SOLID EARTH > TECTONICS > EARTHQUAKES
EARTH SCIENCE > SOLID EARTH > TECTONICS > EARTHQUAKES > EARTHQUAKE PREDICTIONS
tectonic setting > plate margin setting
tectonic setting > plate margin setting > subduction zone setting
tectonic process > subduction
tectonic process
geologic process
deformation
thrust fault
tectonic and structural features
Gelatine > Pig skin
Gelatine
Wedge simulator
Earthquake simulator
Digital Image Correlation (DIC) / Particle Image Velocimetry (PIV) > MatPIV
Videocamera
Surface image

Corresponding MSL vocabulary keywords
subducting plate interface
thrust fault
gelatin
wedge simulator
wedge simulator
fault simulator
video camera
model surface monitoring (2D)

MSL enriched keywords
tectonic plate boundary
convergent tectonic plate boundary
subduction
subducting plate interface
tectonic deformation structure
tectonic fault
thrust fault
analogue modelling material
elastic modelling material
natural elastic material
gelatin
Apparatus
analogue modelling
deformation experiments
wedge simulator
geomorphic experiments
wedge simulator
fault simulator
Ancillary equipment
model surface monitoring (2D)
camera
video camera
Software
digital image correlation (DIC)

Metadata


MSL enriched sub domains

analogue modelling of geologic processes

Resource Type

Dataset


Source


Source publisher

GFZ Data Services

DOI

10.5880/fidgeo.2018.071

Creators

Corbi, Fabio
Personal
Università degli Studi Roma Tre, Rome, Italy
Sandri, Laura
Personal
INGV Bologna
Bedford, Jonathan
Personal
GFZ German Research Centre for Geosciences, Potsdam, Germany
Funiciello, Francesca
Personal
Università degli Studi Roma Tre, Rome, Italy
Brizzi, Silvia
Personal
Università degli Studi Roma Tre, Rome, Italy
Rosenau, Matthias
Personal
GFZ German Research Centre for Geosciences, Potsdam, Germany
Lallemand, Serge
Personal
Géosciences Montpellier, CNRS, Montpellier, France | Montpellier University, Montpellier, France

Contributors

Corbi, Fabio
Personal
Università degli Studi Roma Tre, Rome, Italy
Corbi, Fabio
Personal
Università degli Studi Roma Tre, Rome, Italy
Laboratory Of Experimental Tectonics (University Of Roma TRE, Italy)
Personal
Universitá degli studi "Roma TRE", Rome, Italy

Citation

Corbi, F., Sandri, L., Bedford, J., Funiciello, F., Brizzi, S., Rosenau, M., & Lallemand, S. (2018). Supplementary material to "Machine Learning can predict the timing and size of analog earthquakes" [Data set]. GFZ Data Services. https://doi.org/10.5880/FIDGEO.2018.071


References

URL
References

Dates

Created 2016-01
Issued 2018

Language

en


Funding References

Funder Name H2020 Marie Skłodowska-Curie Actions
Funder Identifier https://doi.org/10.13039/100010665
Award Number 658034
Award Title AspSync
Funder Name Deutsche Forschungsgemeinschaft
Funder Identifier https://doi.org/10.13039/501100001659
Award Number CRC 1114
Award Title Scaling Cascades in Complex Systems
Funder Name Deutsche Forschungsgemeinschaft
Funder Identifier https://doi.org/10.13039/501100001659
Award Number MO-2310/3
Award Title Peascados

Rights

Locations

- no geo-locations found -