A multi-factor approach for process-based seabed characterization: example from the northeastern continental margin of the Korean peninsula (East Sea)

Factors leading to slope failure on a sediment-starved margin: The southwestern continental margin of the East Sea, Korea

“…Contourites and tephra layers have similarly been implicated as a preconditioning factor as interbedded weak layers of similar nature to those described above may act as glide planes (Laberg and Camerlenghi, 2008;Harders et al, 2010;Baeten et al, 2014). Deposition within the slope was likely influenced by bottom-water currents, and a mounded sediment body to the SE of the SL1 at water depths 400-500 m has been interpreted as bottom-current deposits (Cukur et al, 2018). Hence, current circulation patterns in response to the glacioeustatic sea-level changes are likely to result in the presence of contourite deposits along the slope, particularly in areas adjacent to the local bathymetric highs caused by uplift.…”

“…Recent studies also suggest that the compressional tectonism of the southwestern margin of the East Sea margin developed at ca. 3 to 4 Ma and remained active until today as judged by their deformation of the seafloor (Cukur et al, 2018). Ongoing tectonic activity is also evidenced by the occurrence of numerous, medium-scale earthquakes (2.5<Mw<5.4) on the slope adjacent to the slope failures (Fig.…”

“…In contrast, porosity decreases dramatically across this facies interval from ~65% to ~40%. Facies MgmS is interpreted as grain flow deposits derived from continental shelf sands that were driven over the continental shelf edge by mass-wasting events (Cukur et al, 2018).…”

A Novel Sub-Bottom Profiler Seabed Sediment Classification Method Based on BPNN With Biot-Stoll Model and Attenuation-Based Model

“…Some scholars combined SBP with MBES or SSS to identify the different characteristics of sediments, the two systems using in conjunction provide good observation of the stratigraphy and the large-area seabed habitats simultaneously. The joined analysis of seabed surface and sub-bottom datasets substantiated to be an active method for a better comprehension of the properties of seabed sediments and to distinguish acoustically similar groups in diverse bathymetric settings [19][20][21][22].…”