• Ocean and Polar Research
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• v.34 no.2
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• pp.111-123
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• 2012

To understand the phytoplankton community in the eastern part of the Yellow Sea (EYS), in the summer, field survey was conducted at 25 stations in June 2009, and water samples were analyzed using a epifluorescence microscopy, flow cytometry and HPLC method. The EYS could be divided into four areas by a cluster analysis, using phytoplankton group abundances: coastal mixing area, Anma-do area, transition water, and the central Yellow Sea. In the coastal mixing area, water column was well mixed vertically, and phytoplankton was dominated by diatoms, chrysophytes, dinoflagellates and nanoflagellates, showing high abundance ($>10^5\;cells\;l^{-1}$). In Anma-do coastal waters characterized by high dominance of dinoflagellates, high phytoplankton abundance and biomass separated from other coastal mixing area. The southeastern upwelling area was expanded from Jin-do to Heuksan-do, by a tidal mixing and coastal upwelling in the southern area of Manjae-do, and phytoplankton was dominated by benthic diatoms, nanoflagellates and Synechococcus group in this area. Phytoplankton abundance and biomass dominated by pico- and nanophytoplankton were low values in the transition waters and the central Yellow Sea. In the surface of the central Yellow Sea, high dominance of photosynthetic pigments, 19'-hexanoyloxyfucoxanthin and zeaxanthin implies that haptophytes and cyanobacteria could be the dominant group during the summer. These results indicate that the phytoplankton communities in the EYS were significantly affected by the formation of tidal front, thermal stratification, and coastal upwelling showing the differences of physical and chemical characteristics during the summer.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.162-165
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• 2007

Chlorophyll concentration is an important factor for physical oceanography as well as biological oceanography. For these necessity many oceanographic researchers have been investigated it for a long time. But investigation using vessel is very inefficient, on the other hands, ocean color remote sensing is a powerful means to get fine-scale (spatial and temporal scale) measurements of chlorophyll concentration. Geostationary Ocean Color Imager (GOCI), for ocean color sensor, loaded on COMS (Communication, Ocean and Meteorological Satellite), will be launched on late 2008 in Korea. According to the necessity of algorithm for GOCI, we developed chlorophyll algorithm for GOCI in this study. There are two types of chlorophyll algorithms. One is an empirical algorithm using band ratio, and the other one is a fluorescence-based algorithms. To develop GOCI chlorophyll algorithm empirically we used bands centered at 412 nm, 443 nm and 555 nm for the DOM absorption, chlorophyll maximum absorption and for absorption of suspended solid material respectively. For the fluorescence-based algorithm we analyzed in-situ remote sensing reflectance $(R_{rs})$ data using baseline method. Fluorescence Line Height $({\Delta}Flu)$ calculated from $R_{rs}$ at bands centered on 681 nm and 688 nm, and ${\Delta}Flu_{(area)}$ are used for development of algorithm. As a result ${\Delta}Flu_{(area)}$ method leads the best fitting for squared correlation coefficient $(R^2)$.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.236-241
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• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.4 no.1
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• pp.18-24
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• 1999

The satellite image acquired by RADARSAT SAR on August 15, 1996 reveals internal waves in north coastal waters of Cheju Island. It is indicated from the image data, the tidal elevation data, and the bottom topography data, the internal waves seem to be generated by interaction between shallow bottom and tidal currents travelling in the stratified water in the summer time during the tidal changeovers from ebb to flood. The internal waves generated in such condition show patterns of trains of solitons. Probable amplitude of observed solitons is calculated using estimation of the soliton wave length from SAR image data and K-dV equation. Detection of the internal waves is very significant not only to military strategist for underwater maneuvers such as operation of submarines, but also to physical and biological oceanographers. Temporal and spatial variation of the internal waves are needed to be measured by simultaneous in-situ field study together with SAR to examine the nature of these internal waves.

• Journal of the korean society of oceanography
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• v.36 no.1
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• pp.19-26
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• 2001

The biological pump is one of the important pumping mechanisms absorbing CO$_2$ from the atmosphere into the ocean and can be quantified by estimating new production. New production in the open ocean mostly depends on the supply of nitrate from the water below the mixed layer. While nitrate is affected by many biological processes, the helium isotope ($^3$He) is inert and has very simple physical properties. Using the $^3$He flux and the relation between $^3$He and NO${_3}\;{^-}$- within the thermocline, the nitrate flux supporting new production was estimated in the southern East Sea. The average ${\delta}^3$He within the mixed layer was -14$%_o$ and -l5.4$%_o$ in the winter and autumn, respectively. Through the year excess $^3$He occurs in the mixed layer except for a slight depletion of -17$%_o$ in summer. The $^3$He flux of 13$%_o$md$^{-1}$ associated with the concentration gradient at the air-sea interface was calculated from the product of the piston velocity and the excess $^3$He. Tritium decay within the mixed layer could support only 2$%_o$md$^{-1}$ of the flux. Thus, the remaining 11$%_o$md^{-1}$ could be attributed to the flux of tritiugenic $^3$He from the water below the mixed layer. Nitrate and $^3$He were positively correlated within the thermocline layer with the slope of 0.21 ${\mu}$mol kg$^{-1}$ $%_o\;^{-1}$. The annual nitrate flux estimated from the upward flux of $^3$He and the NO$_{3}\;{^-}$-$^3$He relation was 0.8${\pm}$0.2 mol(N) m$^{-2}$yr$^{-1}$. This flux corresponds to an annual new production of 64 g(C) m$^{-2}$yr$^{-1}$, which is consistent with that in the north-west Pacific.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.183-188
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• 2001

The NOAA AVHRR remotely sensed SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the sea near korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple SST images, all of images must be consistent exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which automatically detects cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$3$^{\circ}C$ as a criterion of SST anomalies). The remotely sensed SST data are tuned by comparing remotely sensed data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel and the SST anomalies are studied by statistical method. It was found that the SST anomalies are rather persistent for one or two months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST. In the Markov lprocess model of SST anomalies, autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. The developed algorithm with automatic cloud pixel detection and rediction of future SST is expected to be incorporated to the operational real time service of SST around Korea.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.3
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• pp.277-289
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• 2021

Among various data types obtained from the ocean, the quality controls for abiotic data collected from chemical, physical, and geological field surveys haves already been partially established. Due to the difficulties in standardization of the data collections and basic analyses, however, the quality controls of biotic data are in its early stage. For marine fish, the necessity of quality control is more demanded due to the wide range of data usage, but there are currently no consistent quality control guidelines because of the diversity and scope of data types derived from species-specific and age-specific information throughout various habitats. In this paper, we provide examples of marine fish data utilization and also show methods of the marine fish data collection, limitations of the data collection methods, and suggestions for improving the marine fish data quality. We hope this paper will help to establish the direction of quality control for marine fish data from both fishery-dependent and fishery-independent surveys in Korea in the near future.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.3
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• pp.246-251
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• 2008

The conceptual design evaluation of Deep-Sea Manganese Nodule Miner(DSNM) based on Axiomatic Design was preformed. Functional Requirements(FRs) in functional domain and Design Parameters(DPs) in physical domain were embodied for the given concept design of DSNM. Interactions between FRs and DPs were sequentially analyzed from the first level hierarchy to the lower level hierarchy. The interactions were expressed as design matrices which showed the dependence or independence between FRs and DPs. The results showed that the design of DSNM was not a coupled one, but a decoupled. Finally, it was conceptually verified that DSNM was a good design satisfying the independence axiom of the Axiomatic Design.

• 한국해양학회지
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• v.9 no.2
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• pp.1-9
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• 1974

The vertical distribution and diurnal migration of Evadne nordmanii has been studied at different stations in the Irish Sea. There are many reports that the migrations of planktonic animals tend to be hampered by thermoclines and haloclines. Physical and chemical factors were compared with vertical distribution and diurnal migrations of the animal. Evadne must be essentially an epiplanktonic form with the ability to endure strong light intensity. The animals generally migrated to the very surface layer from their shallow day strata with the decreased of light intensity. During the night their distribution seems rather random or even throughout all the layers, with a tendency to concentrate at the bottom layers, when the water was homogeneous physically and chemically. E. nordmanii may penetrate minor thermoclines and haloclines, but they may avoid chemically distinct waters or possibly currents.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.140-145
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• 2008

We recently developed new offshore observation system using USN buoy, widely used to measure the directional properties of ocean wave, seawater temperature, UV light, longitude and latitude of the buoy using GPS module. This paper also documents the development and implementation of a buoy network for acquisition of data of base station with buoys. The major phases of the project include specification of the network, physical construction of network nodes, software development for control of nodes, and testing of network performance. We described some of the practical issues involved in designing, building and deploying a buoy network for oceanographic monitoring. The paper explains some of the design decisions and their consequences, and some of the lessons learned from a first lesson network trial at sea.