The University of Southampton
×
Filter your search:
University of Southampton Institutional Repository

Distributed acoustic sensing spatiotemporal maps from Cape Muroto

Distributed acoustic sensing spatiotemporal maps from Cape Muroto
Distributed acoustic sensing spatiotemporal maps from Cape Muroto
This dataset contains the raw experimental data that were produced as part of the NERC-funded project with colleagues from JAMSTEC. The data contains around 1500 spatiotemporal maps / waterfall plots. These maps represent strain values obtained from two different Distributed Acoustic Sensing (DAS) devices attached to a subsea fibre optic cable at Cape Muroto in Japan. On the y-axis it is the spatial, while on the x-axis the temporal dimensions. A portion of this Dataset was processed and labelled in order to train a Convolutional Neural Network classifier. This is available in a different dataset: DOI https://doi.org/10.5258/SOTON/D2831
Geodynamics, Tectonic Plates, Distributed Acoustic Sensing, Earthquake monitoring
University of Southampton
Matthaiou, Ioannis
7855a890-8929-4c90-a08c-9672fd7f6fda
Araki, Eiichiro
48fe1389-0977-456f-bc3e-5ba2f3a96d02
Kodaira, Shuichi
98fd4032-ee7d-43a9-b90d-438d3b60d24c
Masoudi, Ali
8073fb9b-2e6c-46c9-89cf-cb8670d76dc0
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78
Brambilla, Gilberto
815d9712-62c7-47d1-8860-9451a363a6c8
Matthaiou, Ioannis
7855a890-8929-4c90-a08c-9672fd7f6fda
Araki, Eiichiro
48fe1389-0977-456f-bc3e-5ba2f3a96d02
Kodaira, Shuichi
98fd4032-ee7d-43a9-b90d-438d3b60d24c
Masoudi, Ali
8073fb9b-2e6c-46c9-89cf-cb8670d76dc0
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78
Brambilla, Gilberto
815d9712-62c7-47d1-8860-9451a363a6c8

(2023) Distributed acoustic sensing spatiotemporal maps from Cape Muroto. University of Southampton doi:10.5258/SOTON/D2841 [Dataset]

Record type: Dataset

Abstract

This dataset contains the raw experimental data that were produced as part of the NERC-funded project with colleagues from JAMSTEC. The data contains around 1500 spatiotemporal maps / waterfall plots. These maps represent strain values obtained from two different Distributed Acoustic Sensing (DAS) devices attached to a subsea fibre optic cable at Cape Muroto in Japan. On the y-axis it is the spatial, while on the x-axis the temporal dimensions. A portion of this Dataset was processed and labelled in order to train a Convolutional Neural Network classifier. This is available in a different dataset: DOI https://doi.org/10.5258/SOTON/D2831

Archive
DAS_data.zip - Dataset
Available under License Creative Commons Attribution.
Download (1GB)
Text
README.txt - Text
Available under License Creative Commons Attribution.
Download (3kB)

More information

Published date: 2023
Keywords: Geodynamics, Tectonic Plates, Distributed Acoustic Sensing, Earthquake monitoring

Identifiers

Local EPrints ID: 483409
URI: http://eprints.soton.ac.uk/id/eprint/483409
DOI: doi:10.5258/SOTON/D2841
PURE UUID: ce84c47c-c222-4ab9-a6ee-492f3ed46e94
ORCID for Ioannis Matthaiou: ORCID iD orcid.org/0009-0009-3603-2999
ORCID for Ali Masoudi: ORCID iD orcid.org/0000-0003-0001-6080
ORCID for Stefano Modafferi: ORCID iD orcid.org/0000-0003-0428-3194
ORCID for Gilberto Brambilla: ORCID iD orcid.org/0000-0002-5730-0499

Catalogue record

Date deposited: 30 Oct 2023 17:43
Last modified: 06 Jun 2024 02:15

Export record

Altmetrics

Contributors

Contributor: Ioannis Matthaiou ORCID iD
Owner: Eiichiro Araki
Owner: Shuichi Kodaira
Owner: Ali Masoudi ORCID iD
Contributor: Stefano Modafferi ORCID iD
Owner: Gilberto Brambilla ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Library staff additional information
Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×