Continuous, High-Resolution Mapping of Coastal Seafloor Sediment Distribution

Sara Innangi,Mirko Di Febbraro,Renato Tonielli,Marco Sacchi,Michele Innangi,Gabriella Di Martino

doi:10.3390/rs14051268

Sara Innangi, Mirko Di Febbraro + Show 4 more

Open Access

https://doi.org/10.3390/rs14051268

Copy DOI

Abstract

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 km2 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.

Highlights

It has been shown that seafloor geology, in particular topography and grain size distribution, can influence benthic community structure and ecological processes at many spatial scales (e.g., [1–7])
There is a strong interest in multiple research disciplines to undertake seafloor geological and/or habitat mapping, and recent studies have presented different modeling approaches for the classification of seabed sediments [15–18]
The modeling approach presented in this research can be seen as an accurate method for high resolution and continuous mapping of loose sediments in the continental shelf, which can be used in several applications from habitat mapping to substrate shifting when the analysis is repeated across time

Summary

Introduction

Studying the spatial and temporal distribution of seabed sediments is a pivotal topic in marine and coastal environmental research, ranging from biological and ecological research to engineering applications. It has been shown that seafloor geology, in particular topography and grain size distribution, can influence benthic community structure and ecological processes at many spatial scales (e.g., [1–7]). There is a strong interest in multiple research disciplines to undertake seafloor geological and/or habitat mapping, and recent studies have presented different modeling approaches for the classification of seabed sediments [15–18]. Such classification approaches have been performed manually based on the experience of operators [4,19,20], while supervised or unsupervised modeling approaches have recently been proposed [10,21–26].

Objectives

Methods

Results

Discussion

Conclusion