We are often tasked with mapping the presence and distribution of Sabellaria spinulosa reef habitat in a marine project area. The protected status of this ecologically and environmentally important habitat makes it vital that developers have high quality information about its distribution to inform planning and operations.
The main tool used in mapping S. spinulosa reef across a large area, and the industry standard, is side scan sonar (SSS). This is a geophysical instrument that uses lateral-facing acoustic transducers towed slowly behind a vessel to image a wide swath of the sea floor along a track. Data from several overlapping tracks can be mosaicked together to build a continuous picture of the seafloor.
The shading and textures in the greyscale image produced by SSS reveal details about the composition of the substrate and the shape of physical seafloor features. Our seabed mapping experts interrogate this information to predict the presence and distribution of different seabed habitats, including S. spinulosa reef. This typically appears in SSS data as a pattern of disconnected sinuous features with alternating high and low reflectivity. However, the pattern is not definitive and can vary considerably in data from different sites and surveys.
SSS data often contains many different patterns and textures, some revealing true variation in the seafloor, but some being artefacts introduced by the data acquisition and processing pipeline. The same features can even appear differently in the data depending on their position relative to the instrument and the conditions at the time. Consequently, confidence in identifying and delineating S. spinulosa reef and other benthic habitats through expert interpretation varies. For this reason it is important to validate an interpretation of acoustic seafloor data with high-confidence information from underwater camera wherever possible.
Our significant experience and in-house expertise at every stage in the design, survey and interpretation processes enables us to deliver high-confidence results for S. spinulosa reef mapping tasks on rapid timescales. And as we continue to develop this field, we are reaching beyond industry standards to incorporate state-of-the-art machine learning and artificial intelligence to enhance our habitat mapping services.
