SWE_of_Bathymetry.m: A geomorphometric tool to automate discrimination between detachment and magmatic seafloor at slow-spreading ridges from shipboard multibeam bathymetry

The shapes and directionality of the oceanic crust at slow-spreading ridges are key to understanding its magmatic or tectonic emplacement. At slow-spreading ridges, magmatic terrain is marked by linearly fault-bounded abyssal hills, while a more tectonic emplacement termed detachment terrain is marked by long-lived detachment faults forming Oceanic Core Complexes (OCCs). However, the quantitative description of the magmatic and detachment regimes is still limited. We develop a novel geomorphometric technique to automate terrain classification based on the parameterisation of the shape, directionality, and curvature of the seafloor. The algorithm consists of two steps: (1) characterising the pattern observed in the horizontal axes by computing the horizontal eigenvalues of the slope vectors at each multibeam cells and (2) building a weight matrix derived from the computed slopes. The eccentricity of the horizontal eigenvalues defines the dipping pattern in the horizontal axes, hence the term slope-weighted eccentricity (SWE). The technique is applied through a moving window and is tested at 12.5°–15.5° N on the Mid-Atlantic Ridge (MAR), where the two distinct modes of spreading occur. The application of this novel geomorphometric technique yields results consistent with published qualitative interpretation and the distribution of seismicity observed from the peak amplitudes of the tertiary waves (T-waves) in the study area. Using the established algorithm, we found that 41% of the seafloor in our study area experienced detachment faulting (up to 28% are identified as OCCs), 25% experienced typical magmatic accretion, and a buffer zone termed extended terrain affects 34% of the seafloor, where the morphology shows a transition from detachment to magmatic spreading or vice versa. These findings provide new insights into seafloor classification based on the observed morphology and the potential to automate such mapping at other slow-spreading ridge regions.