• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.35 no.6
• /
• pp.146-154
• /
• 2023

In this study, the peak wave period T_p and mean wave period T₀₂ and T_{m-1, 0}, which are major parameters for classifying ocean characteristics, were calculated using water surface elevation data observed from the second west coast oceanographic and meteorological observation tower. In addition, the ratio of abnormal data, correlation analysis, and optimal probability density function were estimated. In the case of T_p among the calculated representative periods, the proportion of abnormal data was 5.73% and 0.67% at each point, and T₀₂ was 4.35% and 0.01%. T_{m-1, 0} was found to be 2.82% and 0.03%. Meanwhile, as a result of analyzing the relationship between T₀₂ and T_p, the relationship was calculated to be 0.53 and 0.63 for each point. The relationship between T_{m-1, 0} and T_p was 1.15 and 1.32, respectively, and T₀₂, T_{m-1, 0} was 1.18 and 1.22. As a result of estimating the optimal probability density function of the calculated representative period, T_p followed the 'Log-normal' and 'Normal' distributions at each point, and T₀₂ was 'Gamma', 'Normal' distribution and T_{m-1, 0} showed that 'Log-normal' and 'Normal' distribution were dominant, respectively. It is decided that these results can be used as basic data for wave analysis conducted on the west coast.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1255-1272
• /
• 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 Heritage: History & Science
• /
• v.56 no.3
• /
• pp.174-193
• /
• 2023

Korea is surrounded by the sea and has rivers connecting to it throughout the inland areas, which has been a geographical characteristic since ancient times. As a result, there have been exchanges and conflicts with various countries through the sea, and rivers have facilitated the transportation of ships carrying grain, goods paid for by taxes, and passengers. Since the past, the sea and rivers have had a significant impact on the lives of Koreans. Consequently, it is expected that there are many cultural heritages submerged in the sea and rivers, and continuous efforts are being made to discover and preserve them. Underwater cultural heritage is difficult to discover due to its location in the sea or rivers, making direct visual observation and exploration challenging. To overcome these limitations, various geophysical survey techniques are employed. Geophysical survey methods utilize the physical properties of elastic waves, including their reflection and refraction, to conduct surveys such as bathymetry, underwater topography and strata. These techniques detect the physical characteristics of underwater objects and seafloor formation in the underwater environment, analyze differences, and identify underwater cultural heritage located on or buried in the seabed. Bathymetry uses an echo sounder, and an underwater topography survey uses a side-scan sonar to find underwater artifacts lying on or partially exposed to the seabed, and a marine shallow strata survey uses a sub-bottom profiler to find underwater heritages buried in the seabed. However, the underwater cultural heritage discovered in domestic waters thus far has largely been accidental findings by fishermen, divers, or octopus hunters. This study aims to analyze and summarize the latest research trends in equipment used for underwater cultural heritage exploration, including bathymetric surveys, underwater topography surveys and strata surveys. The goal is to contribute to research on underwater cultural heritage investigation in the domestic context.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.12 no.2
• /
• pp.112-120
• /
• 2007

This paper reviews the use of parasites as 'biological tags' for studying stock analysis of salmonid fishes. Numerous definitions of stock concepts exist, but most of them essentially define a group of fish as having similar biological characteristics and being self-reproducing as stocks. It is important to manage fish stocks for human consumption and sustainable production and especially for salmonid fishes. Because these fry are considered as each country's property, it is necessary to identify and discriminate each fish stock in the open sea. Methods of separating fish stocks are very diverse. Artificial tags, parasites, otoliths scales and genetic characters have been used for stock analysis and each method has advantages and disadvantages. Of these parasites can be good biological tags because they are applied by nature at no cost. Parasites can be infected with susceptible host fishes when they enter into certain areas. Then if they move to the outside and are caught researchers can infer that the fish had been in the endemic area for a period of time during their life. Hence the host fish can be considered as naturally 'tagged' by parasites. However, if they do not pass the parasites-endemic. area, they will harbour no parasites. Therefore, researchers can discriminate each fish stocks and trace their migration routes with these biological tags. In this paper, several examples on the use of parasites as biological tags for studying salmonids, as well as other species, are listed. The advantages and limitations of parasites as biological tags are also discussed. Chum salmon (Oncorhynchus keta), the main salmonid species migrating to Korea, is distributed all around the North Pacific. Korean chum salmon are generally thought to move to the Sea of Okhotsk, the western North Pacific and the Bering Sea. However, there is no clear information on the distribution and migration pathways of Korean chum salmon, and no markers exist for separating them from others yet. Recent Korean chum salmon stock analysis including parasites information are mentioned.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.12 no.4
• /
• pp.305-314
• /
• 2007

We studied spatial and temporal distributions of the phytoplankton and their relationships to physico-chemical environmental factors in the western Jinhae Bay, Korea from November 2003 to August 2004. In most cases, physico-chemical environmental factors showed homogeneous distribution. The phytoplankton communities were composed of mainly diatoms and dinoflagellates, and their standing crops ranged from $16{\times}10^3\;cells\;l^{-1}\;to\;5,845{\times}10^3\;cells\;l^{-1}$ (with a mean value of $555{\times}10^3\;cells\;l^{-1}$). The bloom of phytoplankton was observed in Gohyun Port in the summer. Seasonal variation of phytoplankton standing crops was higher in winter and summer than in spring and autumn. The dominant species were Skeletonema costatum, Akashiwo sanguinea, Pseudo-nitzschia pungens, Dactyliosolen sp., Leptocylindrus danicus, cryptomonads and etc. Especially, S. costatum was predominant in the summer and A. sanguinea (spring and autumn), Pseudo-nitzschia sp. (summer), Guinardia striata (spring), unidentified flagellates (summer) and cryptomonads (spring) appeared to be an opportunistic species. Concentrations of Chl a ranged from $0.6{\mu}g{\cdot}l^{-1}\;to\;16.7{\mu}g{\cdot}l^{-1}$ (with a mean value of $3.4{\mu}g{\cdot}l^{-1}$). The results of the canonical correspondence analysis implies the study area was grouped into the 2 water masses (inner and outer waters of Gohyun Port) and inner waters had higher abundance and Chl a concentration than outer waters. Also, phytoplankton sanding crops were related with temperature, DO and nutrients ($SiO^2$, TN, TP and etc.) in inner waters. Inner water-mass of Gohyun Port expanded between Gacho Is. and Chilchon Is. during the winter.

• Korean Journal of Remote Sensing
• /
• v.40 no.3
• /
• pp.295-305
• /
• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_2
• /
• pp.1565-1576
• /
• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.