• Proceedings of KOSOMES biannual meeting
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• 2003.11a
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• pp.191-193
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• 2003

Temporal and spatial variability of phytoplankton pigment concentrations around the Korea Peninsula was described, using the monthly mean composite images of the SeaWiFS (Sea-Viewing Wide Field-of-View Sensor). The high pigment concentrations appear in the spring and fall in the East Sea The spring bloom in the southern regions (in April) occurs one month in advance in comparison with tint in the northern regions (in May). In summer season, the pigment concentrations are low all over the region in the East Sea And the high pigment concentrations exist yearly around warm stream along the coast of the East Sea, and in the coast of the West Sea and South Sea In particular, the high pigment concentrations linking near the mouth q the Yangze River to coast of South Sea in Korea appear during August to December.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1541-1551
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• 2023

Radiometric calibration is a fundamental step in ocean color remote sensing since the step to derive solar radiance spectrum in visible to near-infrared wavelengths from the sensor-observed electromagnetic signals. Generally, satellite sensor suffers from degradation over the mission period, which results in biases/uncertainties in radiometric calibration and the final ocean products such as water-leaving radiance, chlorophyll-a concentration, and colored dissolved organic matter. Therefore, the importance of radiometric calibration for the continuity of ocean color satellites has been emphasized internationally. This study introduces an approach to improve the radiometric calibration algorithm for the visible bands of the Geostationary Ocean Color Imager-II (GOCI-II) satellite with a focus on stability. Solar Diffuser (SD) measurements were employed as an on-orbit radiometric calibration reference, to obtain the continuous monitoring of absolute gain values. Time series analysis of GOCI-II absolute gains revealed seasonal variations depending on the azimuth angle, as well as long-term trends by possible sensor degradation effects. To resolve the complexities in gain variability, an azimuth angle correction model was developed to eliminate seasonal periodicity, and a sensor degradation correction model was applied to estimate nonlinear trends in the absolute gain parameters. The results demonstrate the effects of the azimuth angle correction and sensor degradation correction model on the spectrum of Top of Atmosphere (TOA) radiance, confirming the capability for improving the long-term stability of GOCI-II data.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 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.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.337-343
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• 2009

1997년 9월부터 2007년 12월까지 인공위성 해색센서 SeaWiFS의 클로로필-$\alpha$ 농도가 가지는 오차 특성을 분석하고 그 원인을 조사하였다. 동해의 클로로필-$\alpha$ 월별 분포에는 비정상적으로 높은 농도값이 스펙클(speckle) 형태로 출현하였다. 스펙클들은 시공간적으로 연계성이 없이 산발적으로 분포하였으며 주변 평균에 대해 $10mg/m^3$ 이상의 편차를 보였다. 스펙클들은 주로 겨울철에 나타났으며 구름 분포와 관련이 있었다. 10년간 월별 운량 분석 결과 겨울철 운량은 다른 계절과 달리 남동해상에 집중적으로 분포하였으며, 운량이 클수록 스펙클의 농도가 크게 나타나는 통계적 특성을 보였다. 특히 스펙클이 나타나는 화소의 각 밴드별 정규화된 수출광량을 분석해 본 결과 짧은 파장 영역(443, 490, 510 nm)은 전체적으로 수출광량이 낮게 나타난 반면 550 nm 밴드는 정상 화소와 유사한 분포를 보였다. 짧은 파장 영역의 낮은 수출광량은 555 nm 밴드에 대한 비율로 구해지는 클로로필-$\alpha$ 농도값을 비정상적으로 증폭시켰으며 SeaWiFS 자료에 스펙클을 유발하였다. 본 연구는 동해의 SeaWiFS 클로로필-$\alpha$ 농도자료가 지니는 스펙클 오차에 대한 문제점을 제기하고 오차 특성 분석을 통해 좀 더 신뢰도 있는 자료를 해양 응용 연구에 사용해야 함을 제시한다.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.367-370
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• 2009

한국해양연구원에서는 2009년 발사 예정인 통신해양기상위성(COMS: Communication, Ocean and Meteorological Satellite)의 해색센서인 정지궤도 해양위성(GOCI: Geostationary Ocean Color Imager) 데이터의 수신, 처리, 배포를 위한 해양위성센터(KOSC: Korea Ocean Satellite Center)를 구축하고 있다. 2005년 "해양위성센터 구축사업"의 시작으로, 전파 수신 환경 등의 조건을 고려하여, 안산에 위치한 한국해양연구원 본원으로 해양위성센터의 위치를 최종 확정하여 구축을 진행하고 있다. 2009년 3월 현재 수신시스템(GDAS: GOCI Data Aquisition System), 자료전처리시스템(IMPS: Image Pre-processing System), 자료처리시스템(GDPS: GOCI Data Processing System), 자료관리 시스템(DMS: Data Management System), 통합감시제어시스템(TMC: Total Management & Controlling System), 기관간 자료교환시스템(EDES: External Data Exchange System) 등이 구축 완료되었고, 위성자료 배포시스템(DDS: Data Distribution System)을 구축하고 있다. 고용량 데이터의 원활한 전송을 위한 데이터센터를 비롯하여 사용자관점에서의 시스템 구축을 추진하고 있으며, 위성 발사 후 사용자 등록을 시작할 계획이다.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.262-276
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• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agenrr of japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy- and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is assumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays very similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• 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).

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1507-1515
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• 2021

If chlorophyll-a is estimated through ocean color remote sensing, it is able to understand the global distribution of phytoplankton and primary production. However, there are missing data in the ocean color observed from the satellites due to the clouds or weather conditions. In thisstudy, the missing data of the GOCI (Geostationary Ocean Color Imager) chlorophyll-a product wasreconstructed by using DINEOF (Data INterpolation Empirical Orthogonal Functions). DINEOF reconstructs the missing data based on spatio-temporal data, and the accuracy was cross-verified by removing a part of the GOCI chlorophyll-a image and comparing it with the reconstructed image. In the study area, the optimal EOF (Empirical Orthogonal Functions) mode for DINEOF wasin 10-13. The temporal and spatialreconstructed data reflected the increasing chlorophyll-a concentration in the afternoon, and the noise of outliers was filtered. Therefore, it is expected that DINEOF is useful to reconstruct the missing images, also it is considered that it is able to use as basic data for monitoring the ocean environment.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.65-70
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• 2007

Red tide is becoming hot issue of environmental problem worldwide since the 1990. Advanced nations, are progressing study that detect red tide area on early time using satellite for sea. But, our country most seashores bends serious. Also because there are a lot of turbid method streams on coast, hard to detect small red tide area by satellite for sea that is low resolution. Also, method by sea color that use one feature of satellite image for sea of existent red tide area detection was most. In this way, have a few feature in image with sea color and it can cause false negative mistake that detect red tide area. Therefore, in this paper, acquired texture information to use GLCM(Gray Level Co occurrence Matrix)'s texture 6 information about high definition land satellite south Coast image. Removed needless component reducing dimension through principal component analysis from this information. And changed into 2 principal component accumulation images, Experiment result 2 principal component conversion accumulation image's eigenvalues were 94.6%. When component with red tide area that uses only sea color image and all principal component image. displayed more correct result. And divided as quantitative,, it compares with turbid stream and the sea that red tide does not exist using statistical feature analysis about texture.

• Journal of the Korean earth science society
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• v.30 no.2
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• pp.234-246
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• 2009

Characteristics of speckle errors of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-${\alpha}$ concentration were analyzed, and its causes were investigated by using SeaWiFS data in the East Sea from September 1997 to December 2007. The speckles with anomalously high concentrations were randomly distributed and showed remarkably high bias of greater than $10mg/m^3$, compared with their neighboring pixels. The speckles tended to appear frequently in winter, which might be related to cloud distribution. Ten-year averaged cloudiness of winter was much higher over the southeastern part, with frequent speckles, than the northwestern part of the East Sea. Statistical analysis results showed that the number of the speckles was increased as cloudiness increased. Normalized water-leaving radiance of the speckle pixel was considerably low at the short wavelengths (443, 490, and 510 nm), whereas the radiance at 555 nm band was normal. These low measurements produced extraordinarily high concentration from the chlorophyll-${\alpha}$ estimation formula. This study presented the speckle errors of SeaWiFS chlorophyll-${\alpha}$ concentration in the East Sea and suggested that more reliable chlorophyll-${\alpha}$ data based on appropriate ocean color remote sensing techniques should be used for the oceanic application researches.