• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.580-585
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• 2009

Harmful Algal Blooms (HABs), caused by Cochlodinium polykrikoides that causative fishery mortality, impact on aquaculture and economic loss appear particularly in summer and fall seasons in the Korean seas. It was studied on characteristics of HABs in the South Sea of Korea by using satellite and in-situ data. The in-situ data encompassed oceanic and meteorological data from July to October 2002-2008 and satellite data from July to October 2002-2006. Chlorophyll concentrations were calculated using Seaviewing Wide Field-of-view Sensor images by an Ocean Color (OC4) algorithm, and HABs were estimated using the Red tide index Chlorophyll Algorithm (RCA). The HAB occurrences were dominant when water temperature was $22.6-28^{\circ}C$ in August. The frequency of the individual numbers during 2002-2008, the HABs more than 1000 cells/ml (alert condition), were 73.57 %. In meteorological data from July to September during 2002-2008, the average precipitation, the mean air temperature, the mean wind speed and direction, and the sunshine were 9.31 mm/day, $24.07^{\circ}C$, 2.34 m/s and easterly, and 1-11 h, respectively. Our results suggest that the upwelling is caused by southwesterly wind in summer season and the Tsushima Warm Current which have influenced on the dispersion and moving of HAB (chlorophyll). In addition, the fresh water from Nakdong River, as the source of nutrients, also influences the occurrence of HABs.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.2
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• pp.38-45
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• 2001

Three lines from $36_{\circ}$ N, $124_{\circ}$ E, and $132_{\circ}$ E of the East Sea and the Yellow Sea were chosen to extract spectra of normalized water leaving radiances. Comparative analysis of the OCTS algorithm and SeaWiFS(OC-2) algorithms was presented here. OCTS algorithm have more overestimate than SeaWiFS(OC-2 algorithm) for detecting chlorophyll concentration. Atmospheric correction algorithm that is excluded the effect of SS in the case 2 water need for long term ocean environmental monitoring of the East Sea and the Yellow Sea. And, considered the effect of CDOM and SS, bio-optical algorithm have to be developed in this research.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.3
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• pp.207-215
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• 2002

Ocean color properties can be quantified by the relationship between the band ratios of the sensor on the ocean color satellites and the measured field ocean color parameters, A tool to determine the abundance of primary organism using the observed ocean color properties from satellite is presented. Coincident to ocean color satellite passes over the Korean waters, the research vessels were deployed to survey the East Sea, the South Sea and the West Sea around the Korean waters, We have been able to have more than 101) data sets containing coincident in situ chlorophyll a and the estimated chlorophyll a derived from SeaWiFS (Sea-viewing Wide Field-of-view Sensor) from february, 1999 to October, 2001. We were able to develop three proper regional algorithms for the East Sea, the South Sea and the West Sea of the Korean peninsula to estimate chlorophyll a, and set up regional algorithms to quantify the suspended solid in the southern sea of the Korean peninsula, Futhermore we were successful in finding out a simple way of estimating chlorophyll a in the turbid water (Case 2 water) using the relationship between in situ chlorophyll a and the estimated chlorophyll a from the processed level 2 data, using the NASA's global algorithm.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.6
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• pp.507-516
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• 2021

In this study, the machine learning which has been widely used in prediction algorithms recently was used. the research point was the CD(chudong) point which was a representative point of Daecheong Lake. Chlorophyll-a(Chl-a) concentration was used as a target variable for algae prediction. to predict the Chl-a concentration, a data set of water quality and quantity factors was consisted. we performed algorithms about random forest and gradient boosting with Python. to perform the algorithms, at first the correlation analysis between Chl-a and water quality and quantity data was studied. we extracted ten factors of high importance for water quality and quantity data. as a result of the algorithm performance index, the gradient boosting showed that RMSE was 2.72 mg/m³ and MSE was 7.40 mg/m³ and R² was 0.66. as a result of the residual analysis, the analysis result of gradient boosting was excellent. as a result of the algorithm execution, the gradient boosting algorithm was excellent. the gradient boosting algorithm was also excellent with 2.44 mg/m³ of RMSE in the machine learning hyperparameter adjustment result.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.557-561
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• 2004

A comparison was made between chlorophyll a from OSMI and SeaWiFS determined with the standard method during the NFRDI's research cruises. The simple algorithm for calibrating and validating of OSMI chlorophyll a as level 2 data in the East China Sea in specially winter season was made by relationship between the estimated chlorophyll a and the measured chlorophyll a in the field. We compared the distributions of OSMI chlorophyll a, sea surface temperature and zooplankton biomass, catch amounts of the Pacific mackerel in the East China Sea.

• Journal of the Korean earth science society
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• v.40 no.4
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• pp.315-328
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• 2019

Since the Coastal Zone Color Scanner (CZCS)/Nimbus-7 was launched in 1978, a variety of studies have been conducted to retrieve ocean color variables from multi-satellites. Several algorithms and formulations have been suggested for estimating ocean color variables based on multi band data at different wavelengths. Chlorophyll-a (chl-a) concentration is one of the most important variables to understand low-level ecosystem in the ocean. To retrieve chl-a concentrations from the satellite observations, an appropriate algorithm depending on water properties is required for each satellite sensor. Most operational empirical algorithms in the global ocean have been developed based on the band-ratio approach, which has the disadvantage of being more adapted to the open ocean than to coastal areas. Alternative algorithms, including the semi-analytical approach, may complement the limits of band-ratio algorithms. As more sensors are planned by various space agencies to monitor the ocean surface, it is expected that continuous monitoring of oceanic ecosystems and environments should be conducted to contribute to the understanding of the oceanic biosphere and the impact of climate change. This study presents an overview of the past and present algorithms for the estimation of chl-a concentration based on multi-satellite data and also presents the prospects for ongoing and upcoming ocean color satellites.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.187-199
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• 2002

Correlation between chlorophyll a in the East China Sea and spectral bands (412, 443, 490, (510), 555, (676, 765)nm) of Ocean Scanning Multi-Spectral Imager (OSMI) including the profile multi-spectral radiometer (PRR-800) was studied. The values of remote sensing reflectance (Rrs) at the bands corresponding to the field chlorophyll $\alpha$ in the East China Sea were much higher than those in clear waters off California, USA. In case of the particle absorptions related to the chlorophyll a concentration at the spectral bands (440, 670nm) were much higher in the East China Sea than the ones in the clean waters off California. The normalized water leaving radiances (nLw) at 412, 443, 490, 555 nm of OSMI and the field chlorophyll a in the East China Sea were correlated each other. According to the results, the relationship between field chlorophyll $\alpha$ and nLw 410 nm in OSMI bands was the lowest, whereas that between field chlorophyll a and nLw 555 nm in the bands was the highest. Reciprocal action between the field chlorophyll a and the band ratio of the OSMI bands (nLw410/nLw555, nLw443/nLw555, nLw490/nLw555) was also studied. Relationship between the chlorophyll $\alpha$ and the band ratio (nLw490/nLw555) was highest in the OSMI bands. Relationship between the chlorophyll $\alpha$ and the ratio (nLw490/nLw555) was higher than one in the nLw410/nLw555. The difference in the estimated chlorophyll $\alpha$ (mg/m$^3$) between OSMI and SeaWiFS (Sea Viewing Wide Field-of-View Sensor) at the special observing stations in the northern eastern sea of Jeju Island in February 25, 2002 was about less than 0.3 mg/m$^3$ within 3 hours. It is suggested that OC2 (ocean color chlorophyll 2 algorithm) be used to get much better estimation of chlorophyll $\alpha$ from OSMI than the ones from the updated algorithms as OC4.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.221-237
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• 2010

To estimate marine primary production, satellite data are essential for providing much better spatial and temporal resolutions. However, primary production estimation for turbid coastal water such as the Yellow Sea still needs much improvement. Here we evaluate currently available methods of primary production estimation in the Yellow Sea. We focus on comparison of eight combinations from four chlorophyll-a algorithms and two primary production algorithms of the Yellow Sea. Estimated primary production by the eight combinations ranged from 96.5 to $610.2\;gC\;m^{-2}\;yr^{-1}$ in the central region of the Yellow Sea. The new chlorophyll algorithms (presently under development by Korea, China, and Japan scientists) are expected to improve the retrieval of chlorophyll-a in turbid regions compared to the standard algorithm but there are certain unresolved problems. The new algorithm for primary production (which uses adjusted physiological parameters with in-situ data) also needs further improvement.

• 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.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.421-434
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• 2012

Colored Dissolved Organic Matter (CDOM) is one of the important components of optical properties of seawater to determine ecosystem dynamics in a given marine area. The optical characteristics of CDOM may depend on the various ecosystem and environmental variables in the sea and those variables may vary region to region. Therefore, the retrieval algorithm for determining light absorption coefficient of CDOM ($a_{CDOM}$) using satellite remote sensing reflectance ($R_{rs}$) developed from other region may not be directly applicable to the other region, and it must be validated using an in-situ ground-truth observation. We have tested 6 known CDOM algorithms (three Semi-analytical and three Empirical CDOM algorithms) developed from other regions of the world ocean with laboratory determined in-situ values for the East Sea using field data collected during seven oceanographic cruises in the period of 2009~2011. Our field measurements extended from the coastal waters to the open oceanic type CASE-1 Waters. Our study showed that Quasi-Analytical Algorithm (QAA_v5) derived $a_{CDOM}$(412) appears to match in-situ $a_{CDOM}$(412) values statistically. Semi-analytical algorithms appeared to underestimate and empirical ones overestimated $a_{CDOM}$ in the East Sea. $a_{CDOM}$(412) value was found to be relatively high in the relatively high satellite derived-chlorophyll-a area. $a_{CDOM}$(412) value appears to be influenced by the amount of chlorophyll-a in seawater. The outcome of this work may be referenced to develop $a_{CDOM}$ algorithm for the new Korean Geostationary Ocean Color Imager (GOCI).