READ ME File For 'Distributed Acoustic Sensing spatiotemporal maps from Cape Muroto'

Dataset DOI: 10.5258/SOTON/D2841

Date that the file was created: October, 2023

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GENERAL INFORMATION
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ReadMe Author: IOANNIS MATTHAIOU, University of Southampton 0009-0009-3603-2999

Date of data collection: September 2022

Information about geographic location of data collection: Cape Muroto, Japan

Related projects: Geodynamics & Tectonics Plate Analysis based on Distributed Optical Fibre Acoustic Sensor

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SHARING/ACCESS INFORMATION
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Licenses/restrictions placed on the data, or limitations of reuse: CC BY

Recommended citation for the data: 
Matthaiou, I., Masoudi, A., Araki, E., Modafferi, S. & Brambilla, G.
'Distributed Acoustic Sensing spatiotemporal maps from Cape Muroto'
September 2022

Links to other publicly accessible locations of the data:

Links/relationships to ancillary or related data sets: 10.5258/SOTON/D2831


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DATA & FILE OVERVIEW
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This dataset contains:

Two subfolders, named "Images_commercial_DAS" and "Images_highresolution_DAS".
 
"Images_commercial_DAS": 
1,461 spatiotemporal maps obtained from a commercial DAS system.

"Images_highresolution_DAS":
16 spatiotemporal maps obtained from a state-of-the-art DAS system, developed
by Dr Ali Masoudi at the University of Southampton.


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METHODOLOGICAL INFORMATION
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Description of methods used for collection/generation of data: 

Distributed Acoustic Sensing (DAS) device was attached, 
to a 50km fibre optic cable that laid on the sea-floor near Cape Muroto, Japan.

The purpose of the system was to detect geophysical activity in the region.

For the high-resolution DAS, for every .33m, a strain value was collected, while
for the commercial DAS, the spatial spacing was 5.1m.

The data were collected for a period of 2 months (approximately) for both the commercial 
and state-of-the-art DAS systems, but, at different time periods.

For the commercial DAS, one spatiotemporal image was stored for every 3 minutes (approximately).
While, for the state-of-the-art DAS spatiotemporal images were generated spanning 9 minutes (approximately).

For more details on the Dataset, including data collection and processing, one can consult
the publication by the same authors:

AUTHORS: Matthaiou, I., Masoudi, A., Araki, E., Modafferi, S. & Brambilla, G.
TITLE: Image classification using ConvNets: a reliable processing tool for fibre optic seismology
JOURNAL: Geophysical Journal International

Methods for processing the data: 

All spatiotemporal maps were post-processed in order to remove unwanted noise from the signals. 
The post-processing includes band-pass filtering and data rescaling to reveal the subtle 
strain values that the fibre optic cable experiences (as disturbances).