• Proceedings of the KSRS Conference
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• v.1
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• pp.224-227
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• 2006

For estimation of three inherent optical properties (IOPs), the absorption coefficients for phytoplankton ($a_{ph}$) and suspended solid particle ($a_{ss}$) and dissolved organic matter ($a_{dom}$), from ocean reflectance, we used inversion of remote sensing reflectance model (Ahn et al., 2001) at this study. The IOP inversion model assumes that (1) the relationship between remote sensing reflectance ($R_{rs}$) and absorption (a) and backscattering ($b_{b}$) is well known, (2) the optical coefficients for pure water ($a_{w}$, $b_{bw}$) are known, (3) the spectral shapes of the specific absorption coefficients for phytoplankton ($a^*_{ph}$) and suspended solid particle ($a^*_{ss}$) and the specific backscattering coefficients for phytoplankton ($b_b^*_{ph}$) and suspended solid particle ($b_b^*_{ss}$) are known. The input data of IOP inversion model is used in-situ ocean optical data at the seawater around the Korea Peninsula for 5 years (2001-2005). We compared the output data of the IOP inversion model and the in-situ observation for seawater around the Korea Peninsula.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.393-398
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• 1998

• Ocean and Polar Research
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• v.43 no.4
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• pp.353-363
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• 2021

Fluorescent dissolved organic matter (FDOM) is referred to organic matter which absorbs efficiently solar radiation energy and fluorescence in the water column. The component and molecular structure of marine organic matter can be changed depending on the various substances and origins of organic matter, and then the organic matter has unique fluorescent properties. As the cutting-edge analytical techniques of optical measurement continuously developing from last few decades, a study on FDOM has been applied as a biogeochemical tracer to quantify the organic matter concentration and to investigate the behaviors and origins of organic matter. Especially, the marine environment around the Korean Peninsula is an ideal research area to study FDOM because of various oceanographic characteristics and the origins of organic matter. This study describes the general properties of FDOM and introduces the cycling and behaviors of marine organic matter based on the domestic research studies.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.445-449
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• 2005

Various methods to detect the phytoplankton/red tide blooms in the oceanic waters have been developed and tested on satellite ocean color imagery since the last two and half decades, but accurate detection of blooms with these methods remains challenging in optically complex turbid waters, mainly because of the eventual interference of absorbing and scattering properties of dissolved organic and particulate inorganic matters with these methods. The present study introduces a new method called Red tide Index (Rl), providing indices which behave as a good measure of detecting red tide algal blooms in high scattering and absorbing waters of the Korean South Sea and Yellow Sea. The effectiveness of this method in identifying and locating red tides is compared with the standard Ocean Chlorophyll 4 (OC4) bio-optical algorithm applied to SeaWiFS ocean imagery, acquired during two bloom episodes on 27 March 2002 and 28 September 2003. The result revealed that OC4 bio-optical algorithm falsely identifies red tide blooms in areas abundance in colored dissolved organic and particulate inorganic matter constituents associated with coastal areas, estuaries and river mouths, whereas red tide index provides improved capability of detecting, predicting and monitoring of these blooms in both clear and turbid waters.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.601-610
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• 2013

As a standard water clarity variable, the vertical underwater visibility, called Secchi depth, is estimated with ocean color satellite data. In the present study, Moderate Resolvtion Imaging Spectradiometer (MODIS) data are used to measure the Secchi depth which is a useful indicator of ocean transparency for estimating the water quality and productivity. To estimate the Secchi depth $Z_v$, the empirical regression model is developed based on the satellite optical data and in-situ data. In the previous study, a semi-analytical algorithm for estimating $Z_v$ was developed and validated for Case 1 and 2 waters in both coastal and oceanic waters using extensive sets of satellite and in-situ data. The algorithm uses the vertical diffuse attenuation coefficient, $K_d$($m^{-1}$) and the beam attenuation coefficient, c($m^{-1}$) obtained from satellite ocean color data to estimate $Z_v$. In this study, the semi-analytical algorithm is validated using temporal MODIS data and in-situ data over the Yellow, Southern and East Seas including Case 1 and 2 waters. Using total 156 matching data, MODIS $Z_v$ data showed about 3.6m RMSE value and 1.7m bias value. The $Z_v$ values of the East Sea and Southern Sea showed higher RMSE than the Yellow Sea. Although the semi-analytical algorithm used the fixed coupling constant (= 6.0) transformed from Inherent Optical Properties (IOP) and Apparent Optical Properties (AOP) to Secchi depth, various coupling constants are needed for different sea types and water depth for the optimum estimation of $Z_v$.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.285-294
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• 1998

A bio-optic survey was made in the Yellow Sea in May, 1998 for OSMI cal/val and application project. Optical measurements were made in nine stations. From these measurements, apparent and inherent optical properties such as $K_d$, R, a, and $b_b$ were estimated. The patterns of reflectance indicated that all three major constituents, namely, chlorophyll-a, suspended sediments, and CDOM were active in determining the optical properties in the Yellow Sea. Their relative contribution was different among the stations. All the stations had high backscattering and their values fell in Case 2 category. Although the total absorption was very high, it could not be explained by the level of CDOM concentration. It is suggested that the suspended sediment might be highly absorptive and further study is needed to investigate the optical properties of the suspended sediments.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.2
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• pp.174-182
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• 1995

Using the optical data from the EUMELI 3 and 4 missions, the optical properties are discussed in relation to primary production in the oligotrophic zone of the Eastern Atlantic Ocean. The depth of euphotic layer $(Z_{eu})$, the total accumulated concentration of pigment $(C_{TOT})$ and the concentration of pigment (C) are 88m, $12.4mgm^{-2}\;and\;0.14mgm^{-3}$, respectively for the EUMELI 3 mission and 101.7m, $10.0mgm^{-2}\;and\;0.10mgm^{-3}$, respectively for the EUMELI 4 mission. The concentration of pigment is higher in autumn (EUMELI 3) than in spring (EUMELI 4). This indicates that the concentration of photosynthetic pigment has a close correlation with vertical attenuation coefficient $(K(\lambda))$ that changes seasonally in the euphotic layer. While the spectral distributions of downward Irradiance$(E_d)$ for the wave length of 470nm increase with depth, those of upward irradiance $(E_u)$ for the wave length range between 410nm and 490nm are constant, because the study area is covered with the blue and clear oceanic deep waters. The vertical attenuation coefficients of downward irradiance $(K_d)$ and upward irradiance $(K_u)$ have low values between 0.02 and $0.06m^{-1}$ due to the low absorption and scattering by the photosynthetic pigment of phytoplankton. Therefore this zone has the characteristics of the case 1 waters with low concentrations of photosynthetic pigment, and can be classifed into IB.

• Proceedings of the KSRS Conference
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• v.1
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• pp.82-85
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• 2006

The Geostationary Ocean Color Imager (GOCI) will be loaded in Communication, Ocean and Meteorological Satellite (COMS). To efficiently apply the GOCI data in the variety of fields, it is essential to develop the standard algorithm for estimating the concentration of ocean environmental components (, , and ). For developing the empirical algorithm, about 300 water samples and in situ measurements were collected from sea water around the Korean peninsula from 1998 to 2006. Two kinds of chlorophyll algorithms are developed by using statistical regression and fluorescence technique considering the bio-optical properties in Case-II waters. The single band algorithm for is derived by relationship between Rrs (555) and in situ concentration. The CDOM is estimated by absorption coefficient and ratio of Rrs(412)/Rrs(555). These standard algorithms will be programmed as a module of GOCI Data Processing System (GDPS) until 2008.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.49.3-49.3
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• 2009

Geostationary Ocean Colour Imager (GOCI) is the first ocean color instrument that will be operating in a geostationary orbit from 2010. GOCI will provide the crucial information of ocean environment around the Korean peninsula in high spatial and temporal resolutions at eight visible bands. We report an on-going development of imaging and radiometric performance prediction model for GOCI with realistic data for reflectance, transmittance, absorption, wave-front error and scattering properties for its optical elements. For performance simulation, Monte Carlo based ray tracing technique was used along the optical path starting from the Sun to the final detector plane for a fixed solar zenith angle. This was then followed by simulation of red-tide evolution detection and their radiance estimation, following the in-orbit operational sequence. The simulation results proves the GOCI flight model is capable of detecting both image and radiance originated from the key ocean phenomena including red tide. The model details and computational process are discussed with implications to other earth observation instruments.