Upslope migrating sand waves on sediment-starved shelves: An example from the southeastern continental margin of the Korean Peninsula

Cukur, Deniz; Kong, Gee-Soo; Buchs, David M.; Lee, Gwang-Soo; Kim, Seong-Pil; Um, In-Kwon; Chun, Jong-Hwa; Kim, Byoung-Yeop; Seo, Ji Eun; Chae, Hyun Sook; Horozal, Senay

doi:10.1016/j.margeo.2021.106728

Cited by 5 publications

(2 citation statements)

References 75 publications

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“…These so‐called bedforms develop at the interface of a flow field and a movable sediment layer. They can be observed in the most diverse environments on Earth and other planetary bodies: from the deep‐sea and continental shelves (Cukur et al., 2022; Franzetti et al., 2013; Reeder et al., 2011) over tidally constrained basins (Armstrong et al., 2021; Hu et al., 2021) to inland streams and rivers (Le Guern et al., 2021; Wu et al., 2021) and even across the barren landscapes of Mars and Titan (Breed et al., 1979; Lorenz et al., 2006). The formation and dynamic behavior of underwater dunes have wide implications for hydrological and morphological processes.…”

Section: Introductionmentioning

confidence: 99%

Automated Bedform Identification—A Meta‐Analysis of Current Methods and the Heterogeneity of Their Outputs

Scheiber,

Zomer,

Wang

et al. 2024

JGR Earth Surface

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Ongoing efforts to characterize underwater dunes have led to a considerable number of freely available tools that identify these bedforms in a (semi‐)automated way. However, these tools differ with regard to their research focus and appear to produce results that are far from unequivocal. We scrutinize this assumption by comparing the results of five recently published dune identification tools in a comprehensive meta‐analysis. Specifically, we analyze dune populations identified in three bathymetries under diverse flow conditions and compare the resulting dune characteristics in a quantitative manner. Besides the impact of underlying definitions, it is shown that the main heterogeneity arises from the consideration of a secondary dune scale, which has a significant influence on statistical distributions. Based on the quantitative results, we discuss the individual strengths and limitations of each algorithm, with the aim of outlining adequate fields of application. However, the concerted bedform analysis and subsequent combination of results have another benefit: the creation of a benchmarking data set which is inherently less biased by individual focus and therefore a valuable instrument for future validations. Nevertheless, it is apparent that the available tools are still very specific and that end‐users would profit by their merging into a universal and modular toolbox.

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Section: Introductionmentioning

confidence: 99%

Automated Bedform Identification—A Meta‐Analysis of Current Methods and the Heterogeneity of Their Outputs

Scheiber,

Zomer,

Wang

et al. 2024

JGR Earth Surface

View full text Add to dashboard Cite

show abstract

“…These so-called bedforms develop at the interface of a flow field and a movable sediment layer. They can be observed in the most diverse environments on Earth and other planetary bodies: from the deepsea and continental shelves (Cukur et al, 2022;Franzetti et al, 2013;Reeder et al, 2011) over tidally-constrained basins (Armstrong et al, 2021;Hu et al, 2021) to inland streams and rivers (Le Guern et al, 2021;Wu et al, 2021) and even across the barren landscapes of Mars and Titan (Breed et al, 1979;Lorenz et al, 2006). The formation and dynamic behavior of underwater dunes have wide implications for hydrological and morphological processes.…”

Section: Introductionmentioning

confidence: 99%

Automated Bedform Identification - A Meta-Analysis of Current Methods and the Heterogeneity of their Outputs

Scheiber,

Zomer,

Wang

et al. 2023

Preprint

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Ongoing efforts to characterize underwater dunes have led to a considerable number of freely available tools that identify these bedforms in a (semi-)automated way. However, these tools differ with regard to their research focus and appear to produce results that are far from unequivocal. We scrutinize this assumption by comparing the results of five recently published dune identification tools in a comprehensive meta-analysis. Specifically, we analyse dune populations identified in three bathymetries under diverse flow conditions and compare the resulting dune characteristics in a quantitative manner. Besides the impact of underlying definitions, it is shown that the main heterogeneity arises from the consideration of a secondary dune scale, which has a significant influence on statistical distributions. Based on the quantitative results, we discuss the individual strengths and limitations of each algorithm, with the aim of outlining adequate fields of application. Yet, the concerted bedform analysis and subsequent combination of results have another benefit: the creation of a benchmarking data set which is inherently less biased by individual focus and therefore a valuable instrument for future validations. Nevertheless, it is apparent that the available tools are still very specific and that end-users would profit by their merging into a universal and modular toolbox.

show abstract

Origin of Subaqueous Dunes on a Flat-topped Seamount, Dokdo in the East (Japan) Sea, Korea

Kim,

Bahk,

Kim

et al. 2024

Ocean Sci. J.

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Upslope migrating sand waves on sediment-starved shelves: An example from the southeastern continental margin of the Korean Peninsula

Cited by 5 publications

References 75 publications

Automated Bedform Identification—A Meta‐Analysis of Current Methods and the Heterogeneity of Their Outputs

Automated Bedform Identification—A Meta‐Analysis of Current Methods and the Heterogeneity of Their Outputs

Automated Bedform Identification - A Meta-Analysis of Current Methods and the Heterogeneity of their Outputs

Origin of Subaqueous Dunes on a Flat-topped Seamount, Dokdo in the East (Japan) Sea, Korea

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