Surficial seabed classification is concerned primarily with distinguishing marine benthic habitat characteristics (e.g. hard, soft, rough, smooth, mud, sand, clay, cobble) of the surveyed area.
[1] Nevertheless, acoustics remain the preferred method of imaging the seafloor because data can be acquired over a much larger area (than in-situ sampling) from almost any depth.
Image processing methods traditionally used in satellite remote sensing are often adapted to quantitatively analyze multibeam backscatter intensity data.
Classification maps are subject to ground-verification in order to identify the compositions and bottom type that characterize each class.
Such data may come from in-situ sediment grab sampling, the use of a dredge, trawl net, visual imagery or surveys using Remotely Operated Vehicles (ROVs).
The seabed classification map can be combined with other information about the area, such as fish distribution and abundance or vegetation characteristics, to establish habitat groups based on associations.