Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach

Bibliographic Details
Main Authors: Booth, A, Christoffersen, P, Pretorius, A, Chapman, J, Hubbard, B, Smith, EC, de Ridder, S, Nowacki, A, Lopvsky, BP, Denolle, M
Format: Article in Journal/Newspaper
Language:unknown
Published: Cambridge University Press 2023
Subjects:
Annals of Glaciology
greenlandic
Online Access:https://eprints.whiterose.ac.uk/196848/
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record_format openpolar
spelling ftleedsuniv:oai:eprints.whiterose.ac.uk:196848 2023-05-15T13:29:39+02:00 Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach Booth, A Christoffersen, P Pretorius, A Chapman, J Hubbard, B Smith, EC de Ridder, S Nowacki, A Lopvsky, BP Denolle, M 2023-02-25 https://eprints.whiterose.ac.uk/196848/ unknown Cambridge University Press Booth, A, Christoffersen, P, Pretorius, A et al. (7 more authors) (Accepted: 2023) Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach. Annals of Glaciology. ISSN 0260-3055 (In Press) Article NonPeerReviewed 2023 ftleedsuniv 2023-03-02T23:17:03Z Article in Journal/Newspaper Annals of Glaciology greenlandic White Rose Research Online (Universities of Leeds, Sheffield & York)
institution Open Polar
collection White Rose Research Online (Universities of Leeds, Sheffield & York)
op_collection_id ftleedsuniv
language unknown
format Article in Journal/Newspaper
author Booth, A
Christoffersen, P
Pretorius, A
Chapman, J
Hubbard, B
Smith, EC
de Ridder, S
Nowacki, A
Lopvsky, BP
Denolle, M
spellingShingle Booth, A
Christoffersen, P
Pretorius, A
Chapman, J
Hubbard, B
Smith, EC
de Ridder, S
Nowacki, A
Lopvsky, BP
Denolle, M
Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach
author_facet Booth, A
Christoffersen, P
Pretorius, A
Chapman, J
Hubbard, B
Smith, EC
de Ridder, S
Nowacki, A
Lopvsky, BP
Denolle, M
author_sort Booth, A
title Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach
title_short Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach
title_full Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach
title_fullStr Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach
title_full_unstemmed Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach
title_sort characterising sediment thickness beneath a greenlandic outlet glacier using distributed acoustic sensing: preliminary observations and progress towards an efficient machine learning approach
publisher Cambridge University Press
publishDate 2023
url https://eprints.whiterose.ac.uk/196848/
genre Annals of Glaciology
greenlandic
genre_facet Annals of Glaciology
greenlandic
op_relation Booth, A, Christoffersen, P, Pretorius, A et al. (7 more authors) (Accepted: 2023) Characterising Sediment Thickness beneath a Greenlandic Outlet Glacier using Distributed Acoustic Sensing: Preliminary Observations and Progress Towards an Efficient Machine Learning Approach. Annals of Glaciology. ISSN 0260-3055 (In Press)
_version_ 1766001770347102208

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