Object-based sample augmentation improves rare-class seabed sediment mapping from multibeam data in the East Sea (Sea of Japan)

Seabed-sediment classification from multibeam echo-sounder data is constrained by sparse, class-imbalanced ground truth, particularly for coarse gravel, which pixel-based classifiers struggle to resolve. This study maps the seabed sediments of the southwestern East Sea (Sea of Japan) continental shelf using object-based sample augmentation, which propagates field-sample labels across Simple Linear Iterative Clustering superpixels of calibrated backscatter and bathymetry. Under 20-seed repeated random cross-validation, object-based augmentation raised the rare-class (Gravel) F1-score from 0.036 for a pixel-only baseline to 0.436, and the gain persisted under spatial-block cross-validation, a within-scene spatial-robustness test on spatially held-out sites (0.024 to 0.311), where SLIC exceeded all tested fixed-neighborhood scales. These rare-class estimates rest on only eight independent Gravel field sites and should be interpreted in that context. Oversampling the original rare-class anchors to the same training size recovered only a minority of this gain, indicating that most of the improvement arose from newly propagated pixels rather than anchor replication. Feature-space and multi-sample diagnostics provided empirical support for the within-superpixel label-propagation assumption. The resulting gravel–sand–mud map reproduces a depth-controlled, fining-offshore facies pattern consistent with hydraulic sorting on the narrow, river-fed shelf. An expert-interpreted Rock assessment further showed that exposed bedrock could not be reliably separated from coarse gravel at an acceptable trade-off in the available single-frequency-per-location backscatter–bathymetry feature space. Overall, the approach recovers rare coarse-substrate facies that pixel-based mapping largely misses while identifying the limits of acoustic-only substrate discrimination, thereby strengthening the baseline seabed-sediment maps that underpin benthic habitat mapping, marine spatial planning, and seabed engineering.

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Publication Details

Journal
Frontiers in Marine Science
Published
2026-10-27
DOI
https://doi.org/10.3389/fmars.2026.1974481
Primary Topic
Underwater Acoustics Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Object-based sample augmentation improves rare-class seabed sediment mapping from multibeam data in the East Sea (Sea of Japan)

Bo‐Yeon Yi, 황선희, Yuri Kim, Seonghoon Moon et al.
2 links
Frontiers in Marine Science
Underwater Acoustics Research
article

Object-based sample augmentation improves rare-class seabed sediment mapping from multibeam data in the East Sea (Sea of Japan)

Bo‐Yeon Yi, 황선희, Yuri Kim, Seonghoon Moon, Eun Je Jeong, Moonsoo Lim, Sungil Kim
article en

Abstract

Seabed-sediment classification from multibeam echo-sounder data is constrained by sparse, class-imbalanced ground truth, particularly for coarse gravel, which pixel-based classifiers struggle to resolve. This study maps the seabed sediments of the southwestern East Sea (Sea of Japan) continental shelf using object-based sample augmentation, which propagates field-sample labels across Simple Linear Iterative Clustering superpixels of calibrated backscatter and bathymetry. Under 20-seed repeated random cross-validation, object-based augmentation raised the rare-class (Gravel) F1-score from 0.036 for a pixel-only baseline to 0.436, and the gain persisted under spatial-block cross-validation, a within-scene spatial-robustness test on spatially held-out sites (0.024 to 0.311), where SLIC exceeded all tested fixed-neighborhood scales. These rare-class estimates rest on only eight independent Gravel field sites and should be interpreted in that context. Oversampling the original rare-class anchors to the same training size recovered only a minority of this gain, indicating that most of the improvement arose from newly propagated pixels rather than anchor replication. Feature-space and multi-sample diagnostics provided empirical support for the within-superpixel label-propagation assumption. The resulting gravel–sand–mud map reproduces a depth-controlled, fining-offshore facies pattern consistent with hydraulic sorting on the narrow, river-fed shelf. An expert-interpreted Rock assessment further showed that exposed bedrock could not be reliably separated from coarse gravel at an acceptable trade-off in the available single-frequency-per-location backscatter–bathymetry feature space. Overall, the approach recovers rare coarse-substrate facies that pixel-based mapping largely misses while identifying the limits of acoustic-only substrate discrimination, thereby strengthening the baseline seabed-sediment maps that underpin benthic habitat mapping, marine spatial planning, and seabed engineering.

Frontiers in Marine ScienceVol. 13
Korea Institute of Ocean Science and Technology (KR), Korea Institute of Geoscience and Mineral Resources (KR), Institute of Marine Research (ES), United States Marine Corps (US)
Korea Institute of Geoscience and Mineral Resources, Korea Institute of Marine Science and Technology promotion
Life below water
Openalex Percentile: Top 18%
Underwater Acoustics Research
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