Seabed sediment classification based on topography-based image partitioning: a case study from the southern Irish Sea

Abstract

Seabed sediment classification is meaningful for seafloor habitat mapping and marine resources exploration. Multibeam Echo-sounding System can acquire backscatter and topographic information, which has become the mainstream for detecting seabed sediment. Because topographic features are closely correlated with sediment distribution, and sediment types tend to be distributed in a continuous pattern, we propose a seabed sediment classification based on topographybased image partitioning. Multi-resolution segmentation and K-means clustering are utilized for image partition based on topographic features, then the classification maps of different subregions are integrated as one result map. The experimental results show that the partitioned methods considerably outperform the global methods in terms of accuracy. This method provides ideas for achieving high-resolution seafloor mapping in the future.