Continuous, High-Resolution Mapping of Coastal Seafloor Sediment Distribution

Seafloor topography and grain size distribution are pivotal features in marine and coastal environments, able to influence benthic community structure and ecological processes at many spatial scales. Accordingly, there is a strong interest in multiple research disciplines to obtain seafloor geological and/or habitat maps. The aim of this study was to provide a novel, automatic and simple model to obtain high-resolution seafloor maps, using backscatter and bathymetric multibeam system data. For this purpose, we calibrated a linear regression model relating grain size distribution values, extracted from samples collected in a 16 km(2) area near Bagnoli-Coroglio (southern Italy), against backscatter and depth-derived covariates. The linear model achieved excellent goodness-of-fit and predictive accuracy, yielding detailed, spatially explicit predictions of grain size. We also showed that a ground-truth sample size as large as 40% of that considered in this study was sufficient to calibrate analogous regression models in different areas. Regardless of some limitations (i.e., inability to predict rocky outcrops and/or seagrass meadows), our modeling approach proved to be a flexible tool whose main advantage is the rendering of a continuous map for sediment size, in lieu of categorical mapping approaches which usually report sharp boundaries or rely on a few sediment classes.

Automated summary

This study presents a novel model for obtaining high-resolution seafloor maps using backscatter and bathymetric multibeam system data. The linear regression model achieved accurate predictions of grain size distribution. Despite some limitations, this modeling approach is a flexible tool that provides continuous maps of sediment size.