In this study, we estimated the distribution density of giant jellyfish in coastal waters of Korea in 2023 and compared the occurrence of giant jellyfish over four years. In May, the giant jellyfish were mainly distributed in the waters of the Yangtze River outflow, and in July, they were highly distributed in the west of Jeju Island and near the south coast of Korea. In addition, when comparing the distribution densities of giant jellyfish in Korea over four years, both acoustic and sighting surveys showed that the highest density of jellyfish occurred in 2021.

In this study, we aimed to determine the seasonal distribution and biomass of fish in Samcheok marine ranching area (MRA) of Republic of Korea using the scientific echosounder. Fish trap and gillnets were used to identify fish species in the survey area, and dB-difference method was used to estimation the spatio-temporal distribution and density of fish. The results showed that the dominant species in Samcheok marine ranching area were Chelidonichthys spinosus, Sebastes inermis, Hexagrammos otakii and Tribolodon hakonensis. The spatio-temporal distribution of fish showed that fish had a relatively higher distribution at night than during the day. In addition, the density of fish by season was highest at night in July at 34.22 g/m 2 and lowest in April at 0.42 g/m 2 .

Acoustics are increasingly regarded as a remote-sensing tool that provides the basis for classifying and mapping ocean resources including seabed classification. It has long been understood that details about the character of the seabed (roughness, sediment type, grain-size distribution, porosity, and material density) are embedded in the acoustical echoes from the seabed. This study developed a sophisticated yet easy-to-use technique to discriminate seabed characteristics using a split beam echosounder. Acoustic survey was conducted in Tongyeong waters, South Korea in June 2018, and the verification of acoustic seabed classification was made by the Van Veen grab sampler. The acoustic scattering signals extracted the seabed hardness and roughness components as well as various seabed features. The seabed features were selected using the principal component analysis, and the seabed classification was performed by the K-means clustering. As a result, three seabed types such as sand, mud, and shell were discriminated. This preliminary study presented feasible application of a sounder to classify the seabed substrates. It can be further developed for characterizing marine habitats on a variety of spatial scales and studying the ecological characteristic of fishes near the habitats.