Integration of machine learning using hydroacoustic techniques and sediment sampling to refine substrate description in the Western Cape, South Africa

Abstract A method to map bio-physical benthic habitats on the continental shelf of South Africa has been developed and is being refined. The goal is to produce a benthic habitat classification method that bridges the disciplines of marine geophysics and biological science, with relevance to all elements of the local substrate, using modern methods. Here, we produced ground-truthed seafloor characterisation maps for two study areas (Koeberg Harbour and Clifton) in the Western Cape, South Africa. Multibeam bathymetry and backscatter data were collected and processed using machine learning clustering techniques. The study area offshore of Clifton was used to test the recently developed k-means clustering algorithm, and Koeberg Harbour, which is 35 km to the north, was used to validate the algorithm because sediment samples, along with drop camera footage, were integrated to better refine the results. Drop-camera footage was classified using the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI) substrata classification scheme and sediment grab samples were processed using a settling tube and formulae based on the Wentworth (1922) and Folk and Ward (1957) statistics. The resulting statistics were used to define the sediment categories that were input into the clustering algorithm. The algorithm results show the distribution of sediment within the respective study areas based on the combination of inputs. Our work uses a stepwise approach from unsupervised methods (previously discussed in Pillay et al., 2020 ), to geological and hydroacoustic verification using ground-truthed data (discussed here), to integrated benthic habitat map production. This work focuses on the second step using hydroacoustic data and ground-truthed geological and sedimentological substrate data to create substrate maps. In the final step further hydroacoustic and biological investigations are needed in order to merge biological and geological habitats, to create benthic habitat maps, along the South African coastline.