• Proceedings of the KSRS Conference
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• v.1
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• pp.170-173
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• 2006

The remote sensing is powerful oceanographic tools not only for Integrated Coastal Zone Management (ICZM) but also for various areas of oceanography. Thank to effort of Government and local authorities as well as active support of international institutions, many projects on the applied oceanography had and have been caring out in coastal and offshore waters of Vietnam sea. One of the modern methods which has been used in these project is ocean color remote sensing technique. This paper will present some preliminary results obtain from application of these techniques in study of coastal and offshore environment of Vietnam sea.

• Proceedings of the KSRS Conference
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• v.1
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• pp.134-134
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• 2006

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.88-91
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• 2008

The COMS IMPS (Communication Ocean and Meteorological Satellite IMage Pre-processing Subsystem) is developed for image pre-processing of COMS. For a test of the COMS IMPS, 7 support software are developed in KARI GS using simulated MI/GOCI WB (Wide-Band) data; COMS Fill Adder, MI (Meteorological Imager) CADU generator, GOCI (Geostationary Ocean Colour Imager) CADU generator, COMS CADU combiner, MI SD (Sensor Data) analyzer, GOCI SD analyzer, and COMS DM (Decomposition Module) test harness. This paper explains functions of developed support software and the COMS IMPS test using those software.

• 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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• 2005.10a
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• pp.108-111
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• 2005

The Communication Ocean, Meteorological Satellite (COMS) as the one of the national space program has been developed by Korea Aerospace Research Institute (KARl). The Geostationary Ocean Color Imager (GOCI) is one of the main payloads ofCOMS which will provide consistent monitoring of ocean-colour around the Korean Peninsula from geostationary platforms. The ocean color observation from geostationary platform is required to remedy the coverage constraints imposed by polar orbiting platforms. In this paper the main characteristics of GOCI are described and compared with the current ocean color sensors. The GOCI will provide the measurement data of 6 visible channels and 2 nearinfrared channels (40Onm - 900nm). The high radiometric sensitivity is essential of ocean color sensor because of the weak water leaving radiance.

• 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.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.505-508
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• 2004

Korea Aerospace Research Institute (KARI) has a plan to launch COMS for consistent monitoring of the Korean Peninsula. Korea Geostationary Ocean Color Imager (GOCI) is one of the main payloads of COMS which will provide a monitoring of ocean-colour around the Korean Peninsula from geostationary platforms. Ocean color observation from geostationary platform is required to achieve the proper spatial and temporal resolution for coastal observation mission. In this paper the characteristics of GOCI and LEO sensors are discussed. GOCI will provide the measurement data of 6 visible channels and 2 near-infrared channels (400nm ~ 900nm). The integration time and aperture diameter required to achieve the SNR specification of KGOCI are analyzed.

• Proceedings of the KSRS Conference
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• v.1
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• pp.463-466
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• 2006

During Mid October of 2005 a mass mortality of the corals occurred surrounding Con Dao Islands (South Vietnam) where is the recognized as one of the most famous marine parks of Vietnam. Results from the field survey in October 2005 showed that the mass mortality of corals and benthos focused only on the North-West of the islands whereas there was almost no death recorded in the South - East parts. Based on field data it was assumed that an overlap between high water temperature ($>30^{\circ}C$) and low salinity (<25%o) during short term was the impact causing the situation. In this paper, we try to explain this phenomenon based on the hydrographical view together with analyzing ocean colour images. A coral bleaching warning system also is proposed for Condao site.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.253-262
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• 2016

Here, we estimated daily Photosynthetically Available Radiation (PAR) from Geostationary Ocean Colour Imager (GOCI) and compared it with daily PAR derived from polar-orbiting MODIS images. GOCI-based PAR was also validated with in-situ measurements from ocean research station, Socheongcho. GOCI PAR showed similar patterns with in-situ measurements for both the clear-sky and cloudy day, whereas MODIS PAR showed irregular patterns at cloudy conditions in some areas where PAR could not be derived due to the clouds of sunglint. GOCI PAR had shown a constant difference with the in-situ measurements, which was corrected using the in-situ measurements obtained on the days of clear-sky conditions at Socheongcho station. After the corrections, GOCI PAR showed a good agreement excepting on the days with so thick cloud that the sensor was optically saturated. This study revealed that GOCI can estimate effectively the daily PAR with its advantages of acquiring data more frequently, eight times a day at an hourly interval in daytime, than other polar orbit ocean colour satellites, which can reduce the uncertainties induced by the existence and movement of the cloud and insufficient images to map the daily PAR at the seas around Korean peninsula.

• Proceedings of the KSRS Conference
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• v.1
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• pp.79-81
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• 2006

Geostationary ocean satellite, unlike other sun-synchronous polar-orbit satellites, will be able to take a picture of a large region several times a day (almost with every one hour interval). For geostationary satellite, the target region is fixed though the location of sun is changed always. Thus, the ocean signal of a given target point is largely dependent on time. In other words, the ocean signal detected by geostationary satellite sensor must translate to the signal of target when both sun and satellite are located in nadir, using another correction model. This correction is performed with a standardization of signal throughout relative geometric relationship among satellite - sun - target points. One signal value of a selected pixel point of the target region of Geostationary Ocean Colour Imager (GOCI) would be set up as a standard, and the ratio of all remained pixel point can be calculated. This relative ratio called bidirectional factor, the result of modelling of spatiotemporal variation of bidirectional factor is shown.