The identification of macroalgal beds is a crucial component for the description of fjord ecosystems. Direct, biological sampling is still the most popular investigation technique but acoustic methods are becoming increasingly recognized as a very efficient tool for the assessment of benthic communities. In 2007 we carried out the first acoustic survey of the littoral areas in Kongsfjorden. A 2.68 km2 area comprised within a 12.40 km2 euphotic zone was mapped along the fjord's coast using single- and multi-beam echosounders. The singlebeam echosounder (SBES) proved to be a very efficient and reliable tool for macroalgae detection in Arctic conditions. The multibeam echosounder (MBES) was very useful in extending the SBES survey range, even though it's ability in discriminating benthic communities was limited. The final result of our investigation is a map of the macroalgae distribution around the fjord, showing 39% macroalgae coverage (1.09 km2) of investigated area between isobaths -0.70 m and -30 m. Zonation analysis showed that most of the studied macroalgae areas occur up to 15 m depth (93%). These results were confirmed by biological sampling and observation in key areas. The potential of acoustic imaging of macrophytes, and a proposed methodology for the processing of acoustic data, are presented in this paper along with preliminary studies on the acoustic reflectivity of macroalgae, also highlighting differences among species. These results can be applied to future monitoring of the evolution of kelp beds in different areas of the Arctic, and in the rest of the world.

Underwater acoustic images are acquired using sonar instrument that uses sound propagation to navigate and map the sea floor. The sonar devices are effectively used to create images of large area of the seabed. However, the visual perception of the object in the acoustic image depends on refraction, which is a function of changes in the speed of sound in successive layers of water. And refraction depends mainly on temperature, slightly on salinity and hydrostatic pressure. The quality and resolution of sonar imaging of the bottom depends on many other factors such as pitch, yaw and heave of the side scan sonar, the presence of volume scatterers in the water body, the distance of the sonar from the bottom and orientation of the object. Generally, the objects in an acoustic image would be of small size compared to their normal size as the distance between the sonar and object is larger. To detect and recognize the objects in the images, the resolution should be enhanced. In this paper, we propose an efficient edge preserving interpolation method for underwater acoustic image resolution enhancement which preserves the edge sharpness. The method handles the diagonal pixels in the first pass, in turn fills the horizontal and vertical pixels in the second pass. The results obtained are compared with the state-of-the-art interpolation techniques and the performance measures such as Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) shows an improved result.