• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.3
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• pp.72-81
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• 2022

Positions of five drifting buoys deployed on August 2020 near southwestern area of Jeju Island and numerically predicted velocities were used to develop five Artificial Intelligence-based models (AI models) for the prediction of particle tracks. Five AI models consisted of three machine learning models (Extra Trees, LightGBM, and Support Vector Machine) and two deep learning models (DNN and RBFN). To evaluate the prediction accuracy for six models, the predicted positions from five AI models and one numerical model were compared with the observed positions from five drifting buoys. Three skills (MAE, RMSE, and NCLS) for the five buoys and their averaged values were calculated. DNN model showed the best prediction accuracy in MAE, RMSE, and NCLS.

• Geophysics and Geophysical Exploration
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• v.27 no.1
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• pp.57-68
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• 2024

Offshore wind power is increasingly regarded as a viable solution for reducing greenhous emissions due to the construction of wind farms and their superior power generation efficiency. Submarine power cables play a crucial role in transmitting the electricity generated offshore to land. To monitor cables and identify points of failure, analyzing the location or depth of burial of submarine cables is necessary. This study reviewed the technology and research for detecting submarine power cables, which were categorized into seismic/acoustic, electromagnetic, and magnetic exploration. Seismic/acoustic waves are primarily used for detecting submarine power cables by installing equipment on ships. Electromagnetic and magnetic exploration detects cables by installing equipment on unmanned underwater vehicles, including autonomous underwater vehicles (AUV) and remotely operated vihicles (ROV). This study serves as a foundational resource in the field of submarine power cable detection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.696-699
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• 2004

A side scan sonar system uses the towfish installed sonars, It is an equipment that search images of the bottom surface of the sea in real time. It is a typical equipment that is related to a sea investigation such as a geological survey, seabed communication cable and power line cable placing repair investigation, fish breeding ground investigation, sea purification, relic and mineral investigation, and mine and submarine search. It used to fined objects and investigate on the seabed surface. But, recently, it is used to sea purification and geological survey that require information of the correct surface of the seabed. So, it needs various filtering technique and image processing techniques development to acquire high resolution image. therefore, this research develops a side scan sonar using multi-beam sensors that supply various information with the fast scan speed and correct high resolution that is not a simple underwater investigation equipment.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.317-318
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• 2006

The towfish oi a side scan sonar is an equipment that search images of the bottom surface of the sea in real time. It is a typical equipment that is related to a sea investigation such as a geological survey, seabed communication cable and power line cable placing repair investigation, fish breeding ground investigation, sea purification, relic and mineral investigation, and mine and submarine search. It used to find objects and Investigate on the seabed surface. But, recently, it is used to sea purification and geological survey that require information of the correct surface of the seabed. So, it needs various filtering technique and image processing techniques development to acquire high resolution image. Therefore, this research develops a side scan sonar using multi-beam sensors that supply various information with the fast scan speed and correct high resolution that is not a simple underwater investigation equipment.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.4
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• pp.294-302
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• 2019

As a series of fundamental researches on the development of an automatic identification monitoring system for fishing gear. Firstly, the study on the installation method of automated identification buoy for the coastal improvement net fishing net with many loss problems on the west coast was carried out. Secondly, the study was conducted find out how to install an automatic identification buoy for coastal gill net which has the highest loss rate among the fisheries. GPS for fishing was used six times in the coastal waters around Seogwipo city in Jeju Island to determine the developmental status and underwater behavior to conduct a field survey. Next, a questionnaire was administered in parallel on the type of loss and the quantity and location of fishing gear to be developed and the water transmitter. In the field experiment, the data collection was possible from a minimum of 13 hours, ten minutes to a maximum of 20 hours and ten minutes using GPS, identifying the development status and underwater behavior of the coastal gillnet fishing gear. The result of the survey showed that the loss of coastal net fishing gear was in the following order: net (27.3%), full fishing gear (24.2%), buoys, and anchors (18.2%). The causes were active algae (50.0%), fish catches (33.3%) and natural disasters (12.5%). To solve this problem, the installation method is to attach one and two electronic buoys to top of each end of the fishing gear, and one underwater transmitter at both ends of the float line connected to the anchor. By identifying and managing abnormal conditions such as damage or loss of fishing gear due to external factors such as potent algae and cutting of fishing gear, loss of fishing gear can be reduced. If the lost fishing gear is found, it will be efficiently collected.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1027-1036
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• 2023

Coastal topographic information is crucial in coastal management, but point measurment based approeaches, which are labor intensive, are generally applied to land and underwater, separately. This study introduces an efficient method enabling land and undetwater surveys using an unmanned aerial vehicle (UAV). This method involves applying two different algorithms to measure the topography on land and water depth, respectively, using UAV imagery and merge them to reconstruct whole coastal digital elevation model. Acquisition of the landside terrain is achieved using the Structure-from-Motion Multi-View Stereo technique with spatial scan imagery. Independently, underwater bathymetry is retrieved by employing a depth inversion technique with a drone-acquired wave field video. After merging the two digital elevation models into a local coordinate, interpolation is performed for areas where terrain measurement is not feasible, ultimately obtaining a continuous nearshore terrain. We applied the proposed survey technique to Jangsa Beach, South Korea, and verified that detailed terrain characteristics, such as berm, can be measured. The proposed UAV-based survey method has significant efficiency in terms of time, cost, and safety compared to existing methods.

• Economic and Environmental Geology
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• v.53 no.6
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• pp.729-742
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• 2020

In this study, we analyze seabottom conditions and characteristics integrated with topographic data, seafloor mosaic, underwater images and orthophoto(drone) of soft-hard bottom area around the Sib-Ri rock in the northern shore of the East Sea(Gyeongpo Beach, Gangneung). We obtained field survey data around the Sib-Ri rock(about 600 m × 600 m). The Sib-Ri rock is formed by two exposed rocks and surrounding reef. The artificial reef zone made by about 200 ~ 300 structures is shown the western area of the Sib-Ri rock. The underwater rock region is extended from the southwestern area of the exposed the Sib-Ri rock with 9 ~ 11 m depth range. The most broad rocky seabottom area is located in the southwestren area of the Sib-Ri rock with 10 ~ 13 m depth range. The study area were classified into 4 types of seabottom environment based on the analysis of bathymetric data, seafloor mosaics, composition of sediments and images(underwater and drone). The underwater rock zones(Type I) are the most distributed area around the Sib-Ri Rock(about 600 m × 600 m). The soft seabottom area made by sediments layer showed 2 types(Type II: gS(gravelly Sand), Type III: S(Sand)) in the areas between underwater rock zones and western part of the Sib-Ri rock(toward Gyeongpo Beach). The artificial reef zone with a lot of structures is located in the western part of the Sib-Ri rock. Marine algae(about 6 species), Phylum porifera(about 2 species), Phylum echinodermata(about 3 species), Phylum mollusca(about 3 species) and Phylum chordata(about 2 species) are dominant faunal group of underwater image analysis area(about 10 m × 10 m) in the northwestern part of the Sib-Ri rock. The habitat of Phylym mollusca(Lottia dorsuosa, Septifer virgatus) and Phylum arthropoda(Pollicipes mitella, Chthamalus challengeri hoek) appears in the intertidal zone of the Sib-Ri rock. And it is possible to estimate the range and distribution of the habitat based on the integrated study of orthphoto(drone) and bathymetry data. The integrated visualization and mapping techniques using seafloor mosaic images, sediments analysis, underwater images, orthophoto(drone) and topographic data can provide and contribute to figure out the seabottom conditions and characteristics in the shore of the East Sea.

• Economic and Environmental Geology
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• v.47 no.5
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• pp.533-540
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• 2014

The Wangdol-cho area, in the Hupo Bank, plays a very important role in main fishing grounds, leisure tourism and marine environmental researches of the East Sea. We analyzed the detailed bathymetry and classified the seabed characteristics of the Wangdol-cho area, based on seafloor backscattering images and sediment grain size. The Hupo Bank is developed in parallel with the eastern coastal line of Korean peninsula, and the shallowest area (Wangdol-cho) of the Hupo Bank is located along the eastern part of Hupo Port. The Wangdol-cho comprises three summits; north summit, middle summit, and south summit. The middle summit area among the three summits has the most shallow water depth with minimum about 6 m. The north summit shows about 8 m minimum depth and the south summit about 9 m. The bathymetry data around three summits represent undulating seabeds with many scattered underwater reefs and shallow water depth. The area between the underwater reefs, the flat seafloor in the northeastern part of the survey site, and the western steep slope area have relatively coarse sediments such as sandy gravel and gravelly sand. The bathymetry in the western side of the Wangdol-cho shows steep slope seabed, extending to the Hupo Basin. Fine sediments including mud and silty sand occur in the Hupo Basin area of the survey site. The submarine detailed topography and the analysis of the seafloor characteristics of the survey area are expected to contribute to management for marine environmental researches and sustainable use of ecosystems in the Wangdol-cho.