• Ocean Science Journal
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• v.42 no.4
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• pp.199-209
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• 2007

Empirical band-ratio algorithms and artificial neural network techniques to retrieve sea surface chlorophyll concentrations were evaluated in the Bohai Sea of China by using an extensive field observation data set. Bohai Sea represents an example of optically complex case II waters with high concentrations of colored dissolved organic mattei (CDOM). The data set includes coincident measurements of radiometric quantities and chlorophyll a concentration (Chl), which were taken on 8 cruises between 2003 and 2005, The data covers a range of variability in Chl in surface waters from 0.3 to 6.5 mg $m^{-3}$. The comparison results showed that these empirical algorithms developed for case I and case II waters can not be applied directly to the Bohai Sea of china, because of significant biases. For example, the mean normalized bias (MNB) for OC4V4 product was 1.85 and the root mean square (RMS) error is 2.26.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.111-115
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• 2001

부유물이 해수의 광특성을 좌우하는 탁한 해수의 해색 분석 알고리즘을 개발하기 위하여 해수의 CASE-II water 원격반사도 모델이 개발되었다. 개발된 원격반사도 모델은 현장관측 자료와 비교 검정되었으며, 모델의 결과를 활용하여 지금까지의 단순 2 band ratio의 클로로필 알고리즘보다 발전된, 즉 부유물 농도의 함수로 새로운 개념의 알고리즘 개발이 시도하였다. 새 해색 클로로필 알고리즘을 SeaWiFS 위성 자료에 적용한 결과 만족스러운 결과를 얻을 수 있었다.

• Ocean Science Journal
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• v.42 no.1
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• pp.49-59
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• 2007

Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield, physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc. Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyll-a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated, the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and new algorithms could be expected.

• 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.39 no.6_2
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• pp.1565-1576
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• 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.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.4
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• pp.359-364
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• 2001

This paper presents case studies on the multi-species fisheries in Korean waters, Multi-species fisheries were divided into two types, that is, multi-species by a single fishery and single species by multiple fisheries. For the case of single species by multiple fisheries, the small yellow croaker stock caught mainly by the Korean pair trawl fishery and the Korean stow net fishery was selected. This approach uses both standardized fishing efforts for the two fisheries by a general linear model and some data for the economic analysis, and then estimates maximum sustainable yield (MSY), maximum economic yield (MEY) and fishing efforts for MSY and MEY, An analysis of interaction aspects between pair trawl and stow net fisheries was carried out to predict the optimal level of fishing effort from the economic point of view, which gives the largest benefits to the two fisheries.

• Proceedings of the KSRS Conference
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• v.1
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• pp.25-28
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• 2006

We propose a new method of masking cloud-affected pixels in satellite ocean color imageries such as of GLI. Those pixels, mostly found around cloud pixels or in scattered cloud area, have anomalous features in either in chlorophyll-a estimate or in water reflectance. This artifact is most likely caused by residual error of inter-band registration correction. Our method is to check the pixel-wise 'soundness' of the spectral water reflectance Rw retrieved after the atmospheric correction. First, we define two spectral ratio between water reflectance, IRR1 and IRR2, each defined as RW(B1)/RW (B3) RW (B3) and as RW (B2)/RW(B4) respectively, where $B1{\sim}B4$ stand for 4 consecutive visible bands. We show that an almost linear relation holds over log-scaled IRR1 and IRR2 for shipmeasured RW data of SeaBAM in situ data set and for GLI cloud-free Level 2 sub-scenes. The method we propose is to utilize this nature, identifying those pixels that show significant discrepancy from that relationship. We apply this method to ADEOS-II/GLI ocean color data to evaluate the performance over Level-2 data, which includes different water types such as case 1, turbid case 2 and coccolithophore bloom waters.

• Journal of Environmental Health Sciences
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• v.28 no.2
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• pp.61-69
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• 2002

Oship stream is located nearby south eastern coasts. This study was performed to find out waters quality modeling and then to predict water quality of Oship stream. Based on survey data, BOD, T-N, T-P calibration and verification result were in good agreement with measured value within mean coefficient variance(MSE) value, which were 13.9%, 9.0%, 26.5% and 19.5%, 12.0%, 16.5%, respectively. Sectional water quality predictions of the main stream of Oship stream are executed on the basis of the following cases 1) with sewage treatment of Dogye-eup 2) reduction of mine wastewater treatment of 80% in th basin. As a result, BOD, T-P improvement rates at down stream of Oship stream, case 1) were appeared 12.2%, 22.2%, case 2) maximum sulfate ion and conductivity reduction removal rate of Oship stream were 58%, 68%. The main pollution sources of Oship-stream were almost domestic wastewater and mine wastewater discharged from Dogye-eup which located in uppers stream. The large effects will appear after the construction of Dogye sewage water treatment plant which remove the organic matter and nutrients in these sewage water. The waste water from mine can not easily to treat for characteristics of effluence and economic problems. However, to achieve the goal of water quality in Oship-stream water system, treatments of those are necessary.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.173-188
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• 2005

The present study aims to derive and compare narrow and broad bandwidths of ocean color sensor’s algorithms for the study of monitoring highly dynamic coastal oceanic environmental parameters using high-resolution imagery acquired from Multi-spectral Camera (MSC) on KOMPSAT-2. These algorithms are derived based on a large data set of remote sensing reflectances ($R_{rs}$) generated by using numerical model that relates $b_b/(a + b_b)$ to $R_{rs}$ as functions of inherent optical properties, such as absorption and backscattering coefficients of six water components including water, phytoplankton (chl), dissolved organic matter (DOM), suspended sediment (SS) concentration, heterotropic organism (he) and an unknown component, possibly represented by bubbles or other particulates unrelated to the first five components. The modeled $R_{rs}$ spectra appear to be consistent with in-situ spectra collected from Korean waters. As Kompsat-2 MSC has similar spectral characteristics with Landsat-5 Thematic Mapper (TM), the model generated $R_{rs}$ values at 2 ㎚ interval are converted to the equivalent remote sensing reflectances at MSC and TM bands. The empirical relationships between the spectral ratios of modeled $R_{rs}$ and chlorophyll concentrations are established in order to derive algorithms for both TM and MSC. Similarly, algorithms are obtained by relating a single band reflectance (band 2) to the suspended sediment concentrations. These algorithms derived by taking into account the narrow and broad spectral bandwidths are compared and assessed. Findings suggest that there was less difference between the broad and narrow band relationships, and the determination coefficient $(r^2)$ for log-transformed data [ N = 500] was interestingly found to be $(r^2)$ = 0.90 for both TM and MSC. Similarly, the determination coefficient for log-transformed data [ N = 500] was 0.93 and 0.92 for TM and MSC respectively. The algorithms presented here are expected to make significant contribution to the enhanced understanding of coastal oceanic environmental parameters using Multi-spectral Camera.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.285-295
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• 2001

We developed a CASE-II water model that will enable the simulation of remote sensing reflectance($R_{rs}$) at the coastal waters for the retrieval of suspended sediments (SS) concentrations from satellite imagery. The model has six components which are: water, chlorophyll, dissolved organic matter (DOM), non-chlorophyllous particles (NC), heterotrophic microorganisms and an unknown component, possibly represented by bubbles or other particulates unrelated to the five first components. We measured $R_{rs}$, concentration of SS and chlorophyll, and absorption of DOM during our field campaigns in Korea. In addition, we generated $R_{rs}$ from different concentrations of SS and chlorophyll, and various absorptions of DOM by random number functions to create a large database to test the model. We assimilated both the computer generated parameters as well as the in-situ measurements in order to reconstruct the reflectance spectra. We validated the model by comparing model-reconstructed spectra with observed spectra. The estimated $R_{rs}$ spectra were used to (1) evaluate the performance of four wavelengths and wavelengths ratios for accurate retrieval of SS. 2) identify the optimum band for SS retrieval, and 3) assess the influence of the SS on the chlorophyll algorithm. The results indicate that single bands at longer wavelengths in visible better results than commonly used channel ratios. The wavelength of 625nm is suggested as a new and optimal wavelength for SS retrieval. Because this wavelength is not available from SeaWiFS, 555nm is offered as an alternative. The presence of SS in coastal areas can lead to overestimation chlorophyll concentrations greater than 20-500%.