• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.239-249
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• 2010

The Geostationary Ocean Color Imager (GOCI) data-processing system (GDPS), which is a software system for satellite data processing and analysis of the first geostationary ocean color observation satellite, has been developed concurrently with the development of th satellite. The GDPS has functions to generate level 2 and 3 oceanographic analytical data, from level 1B data that comprise the total radiance information, by programming a specialized atmospheric algorithm and oceanic analytical algorithms to the software module. The GDPS will be a multiversion system not only as a standard Korea Ocean Satellite Center(KOSC) operational system, but also as a basic GOCI data-processing system for researchers and other users. Additionally, the GDPS will be used to make the GOCI images available for distribution by satellite network, to calculate the lookup table for radiometric calibration coefficients, to divide/mosaic several region images, to analyze time-series satellite data. the developed GDPS system has satisfied the user requirement to complete data production within 30 minutes. This system is expected to be able to be an excellent tool for monitoring both long-term and short-term changes of ocean environmental characteristics.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.131-146
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• 1999

The satellite visible data have been successfully applied to study the ocean color. Another ocean color sensor, the Ocean Scanning Multi-spectral Imager (OSMI) on the Korea Multi-Purpose Satellite (KOMPSAT) will be launched in 1999. In order to understand the characteristics of future OSMI images, we have first discussed the simulation models and procedures in detail, and produced typical patterns of radiances at visible bands by using radiative transfer models. The various simulated images of full satellite passes and Korean local areas for different seasons, water types, and the satellite crossing equator time (CET) are presented to illustrate the distribution of each component of radiance (i.e., aerosol scattering, Rayleigh scattering, sun glitter, water-leaving radiance, and total radiance). A method to evaluate the image quality and availability is then developed by using the characteristics of image defined as the Complex Signal Noise Ratio (CSNR). Meanwhile, a series of CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of OSMI images before the KOMPSAT will be placed in orbit. Finally, the quality and availability of OSMI images are quantitatively analyzed by the simulated CSNR image. It is hoped that the results would be useful to all scientists who are in charge of OSMI mission and to those who plan to use the data from OSMI.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.311-321
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• 2007

The diffuse attenuation coefficient for down-welling irradiance $K_d({\lambda})$, which is the propagation of down-welling irradiance at wavelength ${\lambda}$ from surface to a depth (z) in the ocean, and underwater visibility are important optical parameters for ocean studies. There have been several studies on $K_d({\lambda})$ and underwater visibility around the world, but only a few studies have focused on these properties in the Korean sea. Therefore, in the present study, we studied $K_d({\lambda})$ and underwater visibility around the coastal area of the Yellow Sea, and developed $K_d({\lambda})$ and underwater visibility algorithms for ocean color satellite sensor. For this research we conducted a field campaign around the Yellow Sea from $19{\sim}22$ September, 2006 and there we obtained a set of ocean optical and environmental data. From these datasets the $K_d({\lambda})$ and underwater visibility algorithms were empirically derived and compared with the existing NASA SeaWiFS $K_d({\lambda})$ algorithm and NRL (Naval Research Laboratory) underwater visibility algorithm. Such comparisons over a turbid area showed small difference in the $K_d({\lambda})$ algorithm and constants of our result for underwater visibility algorithm showed slightly higher values.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.1
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• pp.47-54
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• 2009

This research is about the inherent optical properties(IOPs) of algae which is collected from Nam-Hae for basic research of red tide remote sensing technique development. 21 kinds of red tide organisms were cultivated to investigate IOPs of them in the level of laboratory, and specific absorption coefficient of phytoplankton($a^*$) and backscattering coefficient of phytoplankton(${b_b}^*$) are estimated by using spectrophotometer. Absorption spectrums according to species appeared to range from 0.005 to 0.06 ($m^2{\cdot}mg^{-1}$), and the shapes of spectrums were also different. The range of ${b_b}^*$ appeared to be $10^{-2}{\sim}10^{-4}\;m^2{\cdot}mg^{-1}$, which had about 100 times differences between species, and the shape of spectrum have significant difference between species. These results will input as a remote sensing reflectance model input parameter from ocean color.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.377-391
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• 2018

In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.136-136
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• 2010

해색원격탐사에서 해수 type을 광학적 성질에 따라 Case-I water와 Case-II water로 구분한다. Case-I water는 기본적으로 조류 세포 및 그 쇄설물 그리고 미량의 용존 유기물을 포함하며, 맑은 해수인 대양이 이에 속한다. Case-II water는 부유 무기입자, 육상 기원입자 및 높은 용존 유기물 농도, 인간이 만든 유입물을 포함한 탁한 해수이며, 연안 해역의 해수가 이에 속한다(Gordon, 1983). Case-II water에 속하는 연안 해역의 부유사 농도는 해양 연안 환경 변화를 모니터링 할 수 있는 중요한 지표 중 하나이다. 부유사가 연안 환경, 연안 양식장, 어장 환경에 어떤 영향을 주는지 파악할 수 있다. 채수를 통하여 부유사 농도를 추정하는 것은 시간적 경제적 제약이 따른다. 하지만 위성자료와 실측 자료간의 상관관계가 잘 나타나는 계수를 유도하면, 실측없이 위성영상만 있으면 연속적인 부유사 농도 분포를 볼 수 있을 것으로 기대된다. 이런 목적으로 Landsat ETM+ 자료를 이용하여 광양만의 표층 부유사 농도를 추정하였다. 위성 통과시간에 맞춰 2009년 9월 22일과 11월 25일 2차례에 걸쳐 부유사 농도와 반사도를 광양만 16개 정점에서 측정하였다. 부유사 농도는 표층의 해수를 채수하여 GF/F 필터를 이용해 측정되었고, 반사도는 Spectroradiometer를 사용하여 350nm부터 1050nm까지 1nm 간격으로 측정되었다. Landsat ETM+ 자료와 실측 반사도는 원격반사도 $R_{rs}$로 변환되었고, 두 가지 $R_{rs}$를 실측 부유사 농도와 비교하여 부유사 농도 산출 계수를 유도하였다. 경험적으로 구한 계수를 사용하여 위성영상을 부유사 농도로 계산하였으며, 이는 같은 날의 실측 부유사 농도와 비슷한 공간분포를 나타내었다.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.107-120
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• 2011

Several MODIS AQUA products have been compared with shipboard data to assess the possibility of using remote sensing to estimate particulate organic carbon (POC) concentration in the surface waters of the East Sea. A total of 30 POC profiles obtained in spring and summer seasons of the years of 2006~2010 were compared with remote sensing reflectance at various wavelengths and diffuse attenuation coefficient at 490 nm observed by MODIS AQUA. The algorithm thus established was $POC=266.85^*[R_{rs}(488)/R_{rs}(555)]^{-1.447}$ ($R^2=0.924$) with root mean square error of 20.9 mg $m^{-3}$. Remotely sensed POC contents derived using our algorithm appeared also not to be affected by the presence of non-POC component in suspended particulate matter. Therefore this algorithm could be applied to obtain POC concentration over the East Sea using MODIS Aqua observation.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1363-1372
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• 2021

Red tide, defined as the major reproduction of harmful birds, has the characteristics of being generated and diffused in a wide area. This has limitations in detection only with the existing investigation method. Therefore, in this study, red tide was detected using a remote sensing technique. In addition, it was intended to increase the accuracy of detection by using optical characteristics, not just the concentration of chlorophyll. Red tide mainly occurs on the southern coast where sea signals are complex, and the main red tide control species on the southern coast is Cochlodinium polykirkoides. Therefore, it was intended to secure objectivity by reflecting features that could not be found depending on the researcher's observation and experience, not limited to visual judgment using machine learning techniques. In this study, support background machines and random forest were used among machine learning models, and as a result of calculating accuracy as performance evaluation indicators of the two models, the accuracy was 85.7% and 80.2%, respectively.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.175-181
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• 1999

A recurring eddy which located at the terminal end of the Korean East Warm Current was captured on ocean color and sea surface temperature imagery from satellite in spring and autumn. During late April, 1997 thermal infrared imagery from the NOAA AVHRR sensor and ocean color data from the Japanese ADEOS-I OCTS sensor, revealed this feature. The cold core had elevated chlorophyll concentrations, based on OCTS estimates, of greater than 3 mg/m$^3$ while the warmer surrounding waters had chlorophyll concentrations of 1 mg/m$^3$ or less. The elevated cholophyll accociated with this eddy has not been previously described. The eddy is also evident in SST images from autumn, but the SST in the core is warmer than in spring, and the warm jet flowing to the west of the eddy is also warmer is autumn compared to spring. A reccurring eddy and the high chlorophyll_a concentration area which surround around the eddy show on NOAA and SeaWiFS images in March 2, 1998. The eddy forms at the northern extent of the Korean East Warm Current as those waters collide with the cold, south-flowing Liman Current over a topographic shelf about 1500 m deep. This region of the eddy formation appears to have a strong connection with the dynamics of the western part of the polar front eddy field that dominates surface mesoscale structure in the central East (Japan) Sea. Interaction of the eddy with ARGOW tracked drifters, and evidence for its persistence are discussed.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.187-191
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• 2006

This research is about the optical characteristics of algae which is collected from Nam-Hae for basic research of red tide remote sensing technique development 21 kinds of red tide organisms were cultivated to investigate optical characteristics of them in the level of laboratory, and chlorophyll specific absorption coefficient $(a^*)$ and backscattering coefficient $(b_b^*)$ are estimated by using spectrophotometer. Absorption spectrums according to species appeared to range from 0.005 to 0.06 $(m^2/mg)$, and the shapes of spectrums were also different. The range of $b_b^*$ appeared to be $10^{-2}\sim10^{-4}m^2/mg$, which had about 100 times differences between species, and the shape of spectrum have significant difference between species. These results will input as an ocean color model input parameter from ocean color.