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Metadata Files

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)

MSL enriched sub domains i

analogue modelling of geologic processes

Source

https://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=escidoc:3801898

Source publisher

GFZ Data Services


DOI

10.5880/fidgeo.2018.071


Creators

Corbi, Fabio

Università degli Studi Roma Tre, Rome, Italy

ORCID:

https://orcid.org/0000-0003-2662-3065

Sandri, Laura

INGV Bologna

ORCID:

https://orcid.org/0000-0002-3254-2336

Bedford, Jonathan

GFZ German Research Centre for Geosciences, Potsdam, Germany

ORCID:

https://orcid.org/0000-0002-8954-4367

Funiciello, Francesca

Università degli Studi Roma Tre, Rome, Italy

ORCID:

https://orcid.org/0000-0001-7900-8272

Brizzi, Silvia

Università degli Studi Roma Tre, Rome, Italy

ORCID:

https://orcid.org/0000-0002-5258-0495

Rosenau, Matthias

GFZ German Research Centre for Geosciences, Potsdam, Germany

ORCID:

https://orcid.org/0000-0003-1134-5381

Lallemand, Serge

Géosciences Montpellier, CNRS, Montpellier, France | Montpellier University, Montpellier, France

ORCID:

https://orcid.org/0000-0003-1924-9423


Contributors

Corbi, Fabio

ContactPerson

Università degli Studi Roma Tre, Rome, Italy

ORCID:

https://orcid.org/0000-0003-2662-3065

Corbi, Fabio

ContactPerson

Università degli Studi Roma Tre, Rome, Italy

ORCID:

https://orcid.org/0000-0003-2662-3065

Laboratory Of Experimental Tectonics (University Of Roma TRE, Italy)

HostingInstitution

Universitá degli studi "Roma TRE", Rome, Italy


References

10.1029/2018gl081251

10.1002/2017gl074182

http://folk.uio.no/jks/matpiv/html/MatPIVtut.pdf

10.1029/2019gl086615


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


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

Funder identifier type: Crossref Funder ID

Award number: 658034

Award title: AspSync

Funder name: Deutsche Forschungsgemeinschaft

Funder identifier: https://doi.org/10.13039/501100001659

Funder identifier type: Crossref Funder ID

Award number: CRC 1114

Award title: Scaling Cascades in Complex Systems

Funder name: Deutsche Forschungsgemeinschaft

Funder identifier: https://doi.org/10.13039/501100001659

Funder identifier type: Crossref Funder ID

Award number: MO-2310/3

Award title: Peascados


Rights

CC BY 4.0