Seabed Classification is the acoustic remote sensing of ocean, lake, and river bottoms to characterize the physical, geological, and biological properties of the marine floor. Remote sensing is done using almost any sonar, from singlebeam echo sounders to sophisticated multibeam and sidescan imaging sonars. The Maritime Way Acoustic Data Analysis and Interpretation (MADAI) system analyzes the acoustic data from these systems and generates detailed maps of marine floor.
Background on Seabed Classification
Seabed classification is the organization of seabeds into discrete units based on characteristics of the acoustic responses generated by echosounders, multibeam sonars, or sidescan sonars.
Why Seabed Classification?
Seabed mapping can be done visually, mechanically, and acoustically.
All visual methods (divers, video, photography) and mechanical methods (divers, grab samples, cores, probes) are slow and manually intensive, thus expensive and not suited to extensive survey work.
The power of acoustic seabed classification is the ability to apply visual or mechanical classifications over much larger areas than point data alone would allow; that is, the sediment properties obtained from the point samples can be applied with confidence over entire regions that have been mapped acoustically. Therefore, the amount of ground-truth that needs to be collected, visually or mechanically, is dramatically reduced. A small number of samples from each class are adequate to define the entire class.
Single Beam Echosounder
Echosounders (depth sounders) work by broadcasting a short pulse of sound (acoustic energy), called the transmit pulse. The echosounder measures the time it takes for an echo to return from the bottom of the sea/lake/river (hereafter referred to as the seabed). That time is then converted into a water depth by multiplying the speed of sound in water.
However, the echo signal contains a lot more information than just the time of travel. The characteristics of the echo signal are a result of the interaction with the seabed. The shape of the echo signal is particularly influenced by features of the seabed surface and immediate subsurface.
Single Beam Seabed Classification uses acoustic algorithms and statistical analysis to classify the echo signals and thus, provide classification of the seabed.
Multibeam and Sidescan Sonars
It is well known that the characteristics of a sonar backscatter image depend on the bottom type. Even to a novice user, the texture differences between images of rocks, sand, and mud are readily apparent. Differences between silt and clay are less obvious. Statistical processing can capture many of the pertinent details of the interaction between the sound and the bottom and of its vertical relief. Multivariate statistics can then isolate those details that are rich in information about the bottom, producing feature vectors that contain the information necessary for accurate and reliable bottom classifications.
A new approach was developed that extracts information, not from the details of the vertical echo over time but, from the amplitudes and variability of backscatter and statistical characteristics at angles away from the vertical.