Detection of Visual Signatures of Marine Mammals and Fish within Marine Renewable Energy Farms Using Multibeam Imaging Sonar

• Published in: Journal of Marine Science and Engineering
• Main Authors: Francisco, Francisco, Sundberg, Jan
• Format: Article in Journal/Newspaper
• Language: English
• Published: Uppsala universitet, Elektricitetslära 2019
• Subjects: Multibeam imaging sonar; visual signature; marine mammal; seal; fish; marine renewable energy; Other Electrical Engineering; Electronic Engineering; Information Engineering; Annan elektroteknik och elektronik; Orca
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-368876; https://doi.org/10.3390/jmse7020022

Techniques for marine monitoring have evolved greatly over the past decades, making the acquisition of environment data safer, reliable and more efficient. On the other hand, the exploration of marine renewable energy introduced dissimilar ways of exploring the oceans and with that arises the need for new techniques for environmental data acquisition, processing and analysis. Marine energy is mostly harvested in murky and high energetic places where conventional data acquisition techniques are impractical. Modern sonar systems, operating at high frequencies, can acquire detailed images of the underwater environment. Variables such as occurrence, size, class and behaviour of a variety of aquatic species of fish, birds, mammals, coexisting within marine energy sites can be gathered using imaging sonar systems. Although sonar images can provide high level of details, still in most of the cases they are difficult to decipher. Therefore, to facilitate the classification of targets through sonar images, this study introduces a framework of extracting visual features of marine targets that would serve as unique signatures. The acoustic measure of visibility (AVM) is here introduced as an indirect technique of identification and classification of targets by comparing the observed size with a standard value. This information can be used to instruct manual and automatic algorithms for identification and classification of underwater targets using imaging sonar systems. Using image processing algorithms embedded in Proviwer4 and FIJI software, this study found that acoustic images can be effectively used to classify cod, harbour and grey seals, and orcas through their size, shape and swimming behaviour. Data showed that cod occurred as bright, 0.9 m long, ellipsoidal targets shoaling in groups of up to 50 individuals. Harbour seals occurred as bright torpedo-like fast moving target, whereas grey seals occurred as bulky-ellipsoidal targets with serpentine movement. Orca or larger marine mammals occurred with relatively low ...