• 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 Environmental Science International
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• v.15 no.1
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• pp.59-66
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• 2006

High concentration of chlorophyll a occurred around the Ulleung Warm Eddy off Ulleung Island in the East Sea of Korea in spring season. The abnormal distributions of chlorophyll a were captured by satellite remote sensing and measured field data. The temporal and spatial scale of the abnormal distributions were around 20days and 50km diameter off Ullung Island. The anomalies were quantified b)'estimated chlorophyll a derived from OCM and SeaWiFS ocean color data from 2000 to 2004. The origin of abnormal hish concentrations was estimated by this study. It was that suspended material discharged from the Nakdong River and the coastal water located in the southeastern part of Korean Peninsula moved to northeastern coast, and then moved to off Ullung island, The high chlorophyll a concentrations including inorganic materials were accumulated by anticyclonic eddy such as the Ullung Warm Eddy around Ullung island in the East Sea of Korea in spring season.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.11-24
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• 2006

Coastal sea surface temperature (CSST) and meteorological data from January through December 1995 are used to estimate the net surface heat flux and heat content for Sendai Bay. The average annual surface heat flux in the area north of the bay is estimated to be $+35Wm^{-2}$, whereas the southwestern area is estimated to be $+56Wm^{-2}$. Therefore, the net surface heat flux shows a net gain of heat over the whole bay. The largest heat gain occurs near Matsukawaura, where the strong Kuroshio/Oyashio interaction produces anomalously cold SST and wind is more moderate than in other regions of Sendai Bay over most of the year. The lowest heat gain occurs around Tashiro Island, where the temperature difference between air and sea surface is lower and wind is stronger. The heat budget shows that both surface forcing and horizontal advection are potentially important contributors to the seasonal evolution of CSST in the bay. From the A VHRR and SeaWiFS data, it is found that offshore conditions between the bay and Eno Island are different due to the presence of the Ojika Peninsula. It is also shown that the temporal behaviors of SSTs in the bay are closely connected with the air-sea heat flux and offshore conditions.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.649-654
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• 2002

In summer season of 1998, a huge flood occurred around the Yangtze River in the eastern China. The low salinity water less than 28 psu from the river was detected around the southeastern part of the Jeju Island which is located in the southern part of the Korean peninsula. We studied how to detect low salinity water from the Yangtze River, which gives terrible damages to the Korean fisheries. We got the relationships between low surface salinity, turbid water from the Yangtze River and digital ocean color using remote sensing of SeaWiFS satellite in the northern East China Sea in summer seanson of 1998, 1999, 2000 and 2001. The charts of salinity in the northern East China Sea were made by the regenerating of the satellite ocean color data with the formula from the relationships between low salinity, in situ turbid water (transparency) and satellite ocean color.

• 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.

• Proceedings of the KSRS Conference
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• v.1
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• pp.328-331
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• 2006

Eight years of SeaWiFS data quantify variability in the time/space patterns of spring bloom development in the Gulf of Maine (GOM). Maximum and earliest spring bloom are usually observed over Georges Bank, later on the deep basins from the west to the east GOM, and latest development along the eastern Maine coast in cold, tidally mixed water. Pronounced interannual variability of spring bloom timing, spatial position, and magnitude are shown in the GOM. Strongest negative anomalies are present in April 1998 and 2001 over Georges Bank and the eastern GOM, and in January to April of 2005 over the most of GOM. Positive anomalies are strong in April 2001, 2003 and 2004 in varying locations as well as in February and March 1999. It is suggested that interannaul variability in spring phytoplankton bloom concentrations is strongly associated with changes in water mass and stratification which might be influenced by basin-scale forcing due to large climate change.

• Journal of Astronomy and Space Sciences
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• v.17 no.2
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• pp.295-308
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• 2000

OSMI(Ocean Scanning Multi-Spectral Imager) raw image data(Level 0) were acquired and radiometrically corrected. We have applied two methods, using solar & dark calibration data from OSMI sensor and comparing with the SeaWiFS data, to the radiometric correction of OSMI raw image data. First, we could get the values of the gain and the offset for each pixel and each band from comparing the solar & dark calibration data with the solar input radiance values, calculated from the transmittance, BRDF (Bidirectional Reflectance Distribution Function) and the solar incidence angle($\beta$, $\theta$) of OSMI sensor. Applying this calibration data to OSMI raw image data, we got the two odd results, the lower value of the radiometric corrected image data than the expected value, and the Venetian Blind Effect in the radiometric corrected image data. Second, we could get the reasonable results from comparing OSMI raw image data with the SeaWiFS data, and get a new problem of OSMI sensor.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.289-305
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• 2004

Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.450-455
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• 1999

• Proceedings of the KSRS Conference
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• v.1
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• pp.450-453
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• 2006

Hydrographic data including particulate organic carbon (POC) from the Northeastern Gulf of Mexico (NEGOM) study were used along with remotely sensed data obtained from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to develop POC algorithms to estimate POC concentration based on empirical and model-based principal component analysis (PCA) methods. In Case I and II waters empirical maximized simple ratio (MSR) and model-based PCA algorithms using full wavebands (blue, green and red wavelengths) provide more robust estimates of POC. The predicted POC concentrations matched well the spatial and seasonal distributions of POC measured in situ in the Gulf of Mexico. The ease in calculating the MSR algorithm compared to PCA analysis makes MSR the preferred algorithm for routine use. In order to determine the inter-annual variations of POC, MSR algorithms applied to calculate 100 monthly mean values of POC concentrations (September 1997-December 2005). The spatial and temporal variations of POC and sea surface temperature (SST) were analyzed with the empirical orthogonal function (EOF) method. POC estimates showed inter-annual variation in three different locations and may be affected by El $Ni{\tilde{n}}o/Southern$ Oscillation (ENSO) events.