A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data
Multi-frequency backscatter data collected from multibeam echosounders (MBESs) is increasingly becoming available. The ability to collect data at multiple frequencies at the same time is expected to allow for better discrimination between seabed sediments. We propose an extension of the Bayesian met...
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2018
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2-s2.0-85058440635 Gaida T.C.; Ali T.A.T.; Snellen M.; Amiri-Simkooei A.; van Dijk T.A.G.P.; Simons D.G. A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data 2018 Geosciences (Switzerland) 8 12 10.3390/geosciences8120455 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058440635&doi=10.3390%2fgeosciences8120455&partnerID=40&md5=6e72adaa567549360266efd1b695032b Multi-frequency backscatter data collected from multibeam echosounders (MBESs) is increasingly becoming available. The ability to collect data at multiple frequencies at the same time is expected to allow for better discrimination between seabed sediments. We propose an extension of the Bayesian method for seabed classification to multi-frequency backscatter. By combining the information retrieved at single frequencies we produce a multispectral acoustic classification map, which allows us to distinguish more seabed environments. In this study we use three triple-frequency (100, 200, and 400 kHz) backscatter datasets acquired with an R2Sonic 2026 in the Bedford Basin, Canada in 2016 and 2017 and in the Patricia Bay, Canada in 2016. The results are threefold: (1) combining 100 and 400 kHz, in general, reveals the most additional information about the seabed; (2) the use of multiple frequencies allows for a better acoustic discrimination of seabed sediments than single-frequency data; and (3) the optimal frequency selection for acoustic sediment classification depends on the local seabed. However, a quantification of the benefit using multiple frequencies cannot clearly be determined based on the existing ground-truth data. Still, a qualitative comparison and a geological interpretation indicate an improved discrimination between different seabed environments using multi-frequency backscatter. © 2018 by the authors. Licensee MDPI, Basel, Switzerland. MDPI AG 20763263 English Article All Open Access; Gold Open Access |
author |
Gaida T.C.; Ali T.A.T.; Snellen M.; Amiri-Simkooei A.; van Dijk T.A.G.P.; Simons D.G. |
spellingShingle |
Gaida T.C.; Ali T.A.T.; Snellen M.; Amiri-Simkooei A.; van Dijk T.A.G.P.; Simons D.G. A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data |
author_facet |
Gaida T.C.; Ali T.A.T.; Snellen M.; Amiri-Simkooei A.; van Dijk T.A.G.P.; Simons D.G. |
author_sort |
Gaida T.C.; Ali T.A.T.; Snellen M.; Amiri-Simkooei A.; van Dijk T.A.G.P.; Simons D.G. |
title |
A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data |
title_short |
A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data |
title_full |
A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data |
title_fullStr |
A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data |
title_full_unstemmed |
A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data |
title_sort |
A multispectral bayesian classification method for increased acoustic discrimination of seabed sediments using multi-frequency multibeam backscatter data |
publishDate |
2018 |
container_title |
Geosciences (Switzerland) |
container_volume |
8 |
container_issue |
12 |
doi_str_mv |
10.3390/geosciences8120455 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058440635&doi=10.3390%2fgeosciences8120455&partnerID=40&md5=6e72adaa567549360266efd1b695032b |
description |
Multi-frequency backscatter data collected from multibeam echosounders (MBESs) is increasingly becoming available. The ability to collect data at multiple frequencies at the same time is expected to allow for better discrimination between seabed sediments. We propose an extension of the Bayesian method for seabed classification to multi-frequency backscatter. By combining the information retrieved at single frequencies we produce a multispectral acoustic classification map, which allows us to distinguish more seabed environments. In this study we use three triple-frequency (100, 200, and 400 kHz) backscatter datasets acquired with an R2Sonic 2026 in the Bedford Basin, Canada in 2016 and 2017 and in the Patricia Bay, Canada in 2016. The results are threefold: (1) combining 100 and 400 kHz, in general, reveals the most additional information about the seabed; (2) the use of multiple frequencies allows for a better acoustic discrimination of seabed sediments than single-frequency data; and (3) the optimal frequency selection for acoustic sediment classification depends on the local seabed. However, a quantification of the benefit using multiple frequencies cannot clearly be determined based on the existing ground-truth data. Still, a qualitative comparison and a geological interpretation indicate an improved discrimination between different seabed environments using multi-frequency backscatter. © 2018 by the authors. Licensee MDPI, Basel, Switzerland. |
publisher |
MDPI AG |
issn |
20763263 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1814778507997216768 |