Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validation
Accurate seabed sediment classification is essential for mapping marine geological features, assessing benthic habitat, and planning coastal infrastructure. This study investigated the utility of multifrequency multibeam echosounder (MBES) backscatter data for improving seabed sediment classificatio...
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Marine Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2025.1631686/full |
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| author | Moonsoo Lim Jeongwon Kang Sunhee Hwang Eunho Jung Byung-Cheol Kum Jongsin Kim |
| author_facet | Moonsoo Lim Jeongwon Kang Sunhee Hwang Eunho Jung Byung-Cheol Kum Jongsin Kim |
| author_sort | Moonsoo Lim |
| collection | DOAJ |
| description | Accurate seabed sediment classification is essential for mapping marine geological features, assessing benthic habitat, and planning coastal infrastructure. This study investigated the utility of multifrequency multibeam echosounder (MBES) backscatter data for improving seabed sediment classification compared to traditional single-frequency approaches. MBES data were acquired at three frequencies (170, 300, and 450 kHz), and post-processed to produce frequency-specific backscatter mosaics and a composite red–green–blue image. Classification was performed using unsupervised clustering methods, including K-means and isodata clustering, with input vectors composed of normalized backscatter intensities from the three frequencies. The integrated multifrequency approach successfully identified three distinct sediment classes, which were validated using grab samples analyzed for grain size, water content, total organic carbon, and slope. These classes exhibited strong correspondence with underlying geomorphological features and local hydrodynamic regimes, confirming the influence of topography and tidal currents on sediment distribution. Lower-frequency data (170 kHz) were more sensitive to subsurface variability, while higher-frequency data (450 kHz) captured surface texture differences more effectively. The combined use of all three frequencies improved classification performance, particularly in transitional sediment zones where single-frequency methods proved ambiguous. The methodology proved robust across varying water depths, sediment types, and complex seabed terrains, aligning with recent advances in MBES-based sediment mapping and supporting its general applicability for other dynamic coastal systems. These results demonstrate that the use of multifrequency MBES backscatter data enhances the resolution and reliability of sediment classification results, providing a robust framework for high-resolution seabed mapping in dynamic coastal environments. |
| format | Article |
| id | doaj-art-b96ab6097117450db2e8561738794d52 |
| institution | DOAJ |
| issn | 2296-7745 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Marine Science |
| spelling | doaj-art-b96ab6097117450db2e8561738794d522025-08-20T02:47:33ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452025-08-011210.3389/fmars.2025.16316861631686Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validationMoonsoo Lim0Jeongwon Kang1Sunhee Hwang2Eunho Jung3Byung-Cheol Kum4Jongsin Kim5Marine Research Corporation, Busan, Republic of KoreaKorea Institute of Ocean Science and Technology (KIOST), Busan, Republic of KoreaMarine Research Corporation, Busan, Republic of KoreaKorea Hydrographic and Oceanographic Agency (KHOA), Busan, Republic of KoreaKorea Institute of Ocean Science and Technology (KIOST), Busan, Republic of KoreaMarine Research Corporation, Busan, Republic of KoreaAccurate seabed sediment classification is essential for mapping marine geological features, assessing benthic habitat, and planning coastal infrastructure. This study investigated the utility of multifrequency multibeam echosounder (MBES) backscatter data for improving seabed sediment classification compared to traditional single-frequency approaches. MBES data were acquired at three frequencies (170, 300, and 450 kHz), and post-processed to produce frequency-specific backscatter mosaics and a composite red–green–blue image. Classification was performed using unsupervised clustering methods, including K-means and isodata clustering, with input vectors composed of normalized backscatter intensities from the three frequencies. The integrated multifrequency approach successfully identified three distinct sediment classes, which were validated using grab samples analyzed for grain size, water content, total organic carbon, and slope. These classes exhibited strong correspondence with underlying geomorphological features and local hydrodynamic regimes, confirming the influence of topography and tidal currents on sediment distribution. Lower-frequency data (170 kHz) were more sensitive to subsurface variability, while higher-frequency data (450 kHz) captured surface texture differences more effectively. The combined use of all three frequencies improved classification performance, particularly in transitional sediment zones where single-frequency methods proved ambiguous. The methodology proved robust across varying water depths, sediment types, and complex seabed terrains, aligning with recent advances in MBES-based sediment mapping and supporting its general applicability for other dynamic coastal systems. These results demonstrate that the use of multifrequency MBES backscatter data enhances the resolution and reliability of sediment classification results, providing a robust framework for high-resolution seabed mapping in dynamic coastal environments.https://www.frontiersin.org/articles/10.3389/fmars.2025.1631686/fullmultibeam echosounderbackscatter classificationmultifrequency acousticsseabed sedimentsK-means clustering |
| spellingShingle | Moonsoo Lim Jeongwon Kang Sunhee Hwang Eunho Jung Byung-Cheol Kum Jongsin Kim Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validation Frontiers in Marine Science multibeam echosounder backscatter classification multifrequency acoustics seabed sediments K-means clustering |
| title | Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validation |
| title_full | Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validation |
| title_fullStr | Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validation |
| title_full_unstemmed | Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validation |
| title_short | Multifrequency backscatter classification of seabed sediments using MBES: an integrated approach with ground-truth validation |
| title_sort | multifrequency backscatter classification of seabed sediments using mbes an integrated approach with ground truth validation |
| topic | multibeam echosounder backscatter classification multifrequency acoustics seabed sediments K-means clustering |
| url | https://www.frontiersin.org/articles/10.3389/fmars.2025.1631686/full |
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