Compression of Multibeam Echosounders Bathymetry and Water Column Data

Over the past decade, Multibeam Echosounders (MBES) have become one of the most used techniques in sea exploration. Modern MBES are capable of acquiring both bathymetric information on the seafloor and the reflectivity of the seafloor and water column. Water column imaging MBES surveys acquire signi...

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Detalles Bibliográficos
Autores: Martí, Aniol, Portell i de Mora, Jordi, Amblàs i Novellas, David, de Cabrera, Ferran, Vilà, Marc, Riba, Jaume, Mitchell, Garrett
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/195371
Acceso en línea:https://hdl.handle.net/2445/195371
Access Level:acceso abierto
Palabra clave:Fons marins
Geologia submarina
Ocean bottom
Submarine geology
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spelling Compression of Multibeam Echosounders Bathymetry and Water Column DataMartí, AniolPortell i de Mora, JordiAmblàs i Novellas, Davidde Cabrera, FerranVilà, MarcRiba, JaumeMitchell, GarrettFons marinsGeologia submarinaOcean bottomSubmarine geologyOver the past decade, Multibeam Echosounders (MBES) have become one of the most used techniques in sea exploration. Modern MBES are capable of acquiring both bathymetric information on the seafloor and the reflectivity of the seafloor and water column. Water column imaging MBES surveys acquire significant amounts of data with rates that can exceed several GB/h depending on the ping rate. These large file sizes obtained from recording the full water column backscatter make remote transmission difficult if not prohibitive with current technology and bandwidth limitations. In this paper, we propose an algorithm to decorrelate water column and bathymetry data, focusing on the KMALL format released by Kongsberg Maritime in 2019. The pre-processing stage is integrated into FAPEC, a data compressor originally designed for space missions. Here, we test the algorithm with three different datasets: two of them provided by Kongsberg Maritime and one dataset from the Gulf of Mexico provided by Fugro USA Marine. We show that FAPEC achieves good compression ratios at high speeds using the pre-processing stage proposed in this paper. We also show the advantages of FAPEC over other lossless compressors as well as the quality of the reconstructed water column image after lossy compression at different levels. Lastly, we test the performance of the pre-processing stage, without the constraint of an entropy encoder, by means of the histograms of the original samples and the prediction errorsMDPI2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/195371Articles publicats en revistes (Dinàmica de la Terra i l'Oceà)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.3390/rs14092063Remote Sensing, 2022, vol. 14, num. 9, p. 2063https://doi.org/10.3390/rs14092063cc-by (c) Martí, Aniol et al., 2022https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1953712026-05-27T06:46:51Z
dc.title.none.fl_str_mv Compression of Multibeam Echosounders Bathymetry and Water Column Data
title Compression of Multibeam Echosounders Bathymetry and Water Column Data
spellingShingle Compression of Multibeam Echosounders Bathymetry and Water Column Data
Martí, Aniol
Fons marins
Geologia submarina
Ocean bottom
Submarine geology
title_short Compression of Multibeam Echosounders Bathymetry and Water Column Data
title_full Compression of Multibeam Echosounders Bathymetry and Water Column Data
title_fullStr Compression of Multibeam Echosounders Bathymetry and Water Column Data
title_full_unstemmed Compression of Multibeam Echosounders Bathymetry and Water Column Data
title_sort Compression of Multibeam Echosounders Bathymetry and Water Column Data
dc.creator.none.fl_str_mv Martí, Aniol
Portell i de Mora, Jordi
Amblàs i Novellas, David
de Cabrera, Ferran
Vilà, Marc
Riba, Jaume
Mitchell, Garrett
author Martí, Aniol
author_facet Martí, Aniol
Portell i de Mora, Jordi
Amblàs i Novellas, David
de Cabrera, Ferran
Vilà, Marc
Riba, Jaume
Mitchell, Garrett
author_role author
author2 Portell i de Mora, Jordi
Amblàs i Novellas, David
de Cabrera, Ferran
Vilà, Marc
Riba, Jaume
Mitchell, Garrett
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Fons marins
Geologia submarina
Ocean bottom
Submarine geology
topic Fons marins
Geologia submarina
Ocean bottom
Submarine geology
description Over the past decade, Multibeam Echosounders (MBES) have become one of the most used techniques in sea exploration. Modern MBES are capable of acquiring both bathymetric information on the seafloor and the reflectivity of the seafloor and water column. Water column imaging MBES surveys acquire significant amounts of data with rates that can exceed several GB/h depending on the ping rate. These large file sizes obtained from recording the full water column backscatter make remote transmission difficult if not prohibitive with current technology and bandwidth limitations. In this paper, we propose an algorithm to decorrelate water column and bathymetry data, focusing on the KMALL format released by Kongsberg Maritime in 2019. The pre-processing stage is integrated into FAPEC, a data compressor originally designed for space missions. Here, we test the algorithm with three different datasets: two of them provided by Kongsberg Maritime and one dataset from the Gulf of Mexico provided by Fugro USA Marine. We show that FAPEC achieves good compression ratios at high speeds using the pre-processing stage proposed in this paper. We also show the advantages of FAPEC over other lossless compressors as well as the quality of the reconstructed water column image after lossy compression at different levels. Lastly, we test the performance of the pre-processing stage, without the constraint of an entropy encoder, by means of the histograms of the original samples and the prediction errors
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/195371
url https://hdl.handle.net/2445/195371
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.3390/rs14092063
Remote Sensing, 2022, vol. 14, num. 9, p. 2063
https://doi.org/10.3390/rs14092063
dc.rights.none.fl_str_mv cc-by (c) Martí, Aniol et al., 2022
https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Martí, Aniol et al., 2022
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Articles publicats en revistes (Dinàmica de la Terra i l'Oceà)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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