• 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.

• Korean Journal of Remote Sensing
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• v.15 no.4
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• pp.367-375
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• 1999

This paper describes the development, operations, and applications of ROCSAT-l and its Ocean Color Imager (OCI) remote-sensing payload. It is the first satellite program of NSPO. The satellite was successfully launched by Lockheed Martin's Athena on January 26, 1999 from Cape Canaveral, Florida. ROCSAT-l is a Low Earth Orbit (LEO) experimental satellite. Its circular orbit has an altitude of 600km and an inclination angle of 35 degrees. The satellite is designed to carry out scientific research missions, including ocean color imaging, experiments on ionospheric plasma and electrodynamics, and experiments using Ka-band (20∼30GHz) communication payloads. The OCI payload is utilized to observe the ocean color in 7 bands (including one redundant band) of Visible and Near-Infrared (434nm∼889nm) range with the resolution of 800m at nadir and the swath of 702km. It employs high performance telecentric optics, push-broom scanning method using Charge Coupled Devices (CCD) and large-scale integrated circuit chips. The water leaving radiance is estimated from the total inputs to the OCI, including the atmospheric scattering. The post-process estimates the water leaving radiance and generates different end products. The OCI has taken images since February 1999 after completing the early orbit checkout. Analyses have been performed to evaluate the performances of the instrument in orbit and to compare them with the pre-launch test results. This paper also briefly describes the ROCSAT-l mission operations. The spacecraft operating modes and ROCSAT Ground Segment operations are delineated, and the overall initial operations of ROCSAT-l are summarized.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.307-312
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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 Agency 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 as-sumed 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 vey 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.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.29 no.2
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• pp.173-182
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• 2013

The early Sea-viewing Wide Field-of-view Sensor(SeaWiFS) atmospheric correction algorithm which is the basis of the atmospheric correction algorithm for Geostationary Ocean Color Imager(GOCI) assumes that water-leaving radiances is negligible at near-infrared(NIR) wavelengths. For this reason, all of the satellite measured radiances at the NIR wavelengths are assigned to aerosol radiances. However that assumption would cause underestimation of water-leaving radiances if it were applied to turbid Case-2 waters. To overcome this problem, Management Unit of the North Sea Mathematical Models(MUMM) atmospheric correction algorithm has been developed for turbid waters. This MUMM algorithm introduces new parameter ${\alpha}$, representing the ratio of water-leaving reflectance at the NIR wavelengths. ${\alpha}$ is calculated by statistical method and is assumed to be constant throughout the study area. Using this algorithm, we can obtain comparatively accurate water-leaving radiances in the moderately turbid waters where the NIR water-leaving reflectance is less than approximately 0.01. However, this algorithm still underestimates the water-leaving radiances at the extremely turbid water since the ratio of water-leaving radiance at two NIR wavelengths, ${\alpha}$ is changed with concentration of suspended particles. In this study, we modified the MUMM algorithm to calculate appropriate value for ${\alpha}$ using an iterative technique. As a result, the accuracy of water-leaving reflectance has been significantly improved. Specifically, the results show that the Root Mean Square Error(RMSE) of the modified MUMM algorithm was 0.002 while that of the MUMM algorithm was 0.0048.

• Proceedings of KOSOMES biannual meeting
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• 2009.06a
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• pp.53-54
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• 2009

The influence of atmospheric aerosol on satellite ocean color data were evaluated using SeaWiFS monthly standard mapped image products. The atmospheric optical thickness (AOT) was increased in spring and summer, and it showed the strong positive correlation with remote sensing reflectance, normalized waterleaving radiance /solar irradiance, at 555 nm (Rrs555) which is a component of the satellite chlorophyll estimation. Such the high AOT and high Rrs555 pixels showed overestimation of satellite chlorophyll in spring, especially in the area which showed large phytoplankton absorption which 1s expressed by low remote sensing reflectance at 443, 490 and 510 nm (Rrs 443, Rrs490 and Rrs510).

• Proceedings of the KSRS Conference
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• v.1
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• pp.467-470
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• 2006

Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meteorological Satellite (COMS) is scheduled for launch in 2008. GOCI includes the eight visible-to-near-infrared (NIR) bands, 0.5km pixel resolution, and a coverage region of 2500 ${\times}$ 2500km centered at 36N and 130E. GOCI has had the scope of its objectives broadened to understand the role of the oceans and ocean productivity in the climate system, biogeochemical variables, geological and biological response to physical dynamics and to detect and monitor toxic algal blooms of notable extension through observations of ocean color. To achieve these mission objectives, it is necessary to develop an atmospheric correction technique which is capable of delivering geophysical products, particularly for highly turbid coastal regions that are often dominated by strongly absorbing aerosols from the adjacent continental/desert areas. In this paper, we present a more realistic and cost-effective atmospheric correction method which takes into account the contribution of NIR radiances and include specialized models for strongly absorbing aerosols. This method was tested extensively on SeaWiFS ocean color imagery acquired over the Northwest Pacific waters. While the standard SeaWiFS atmospheric correction algorithm showed a pronounced overcorrection in the violet/blue or a complete failure in the presence of strongly absorbing aerosols (Asian dust or Yellow dust) over these regions, the new method was able to retrieve the water-leaving radiance and chlorophyll concentrations that were consistent with the in-situ observations. Such comparison demonstrated the efficiency of the new method in terms of removing the effects of highly absorbing aerosols and improving the accuracy of water-leaving radiance and chlorophyll retrievals with SeaWiFS imagery.

• 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.

• Proceedings of the KSRS Conference
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• v.1
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• pp.441-444
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• 2006

The MERIS MCI (Maximum Chlorophyll Index), measuring the radiance peak at 709 nm in water-leaving radiance, indicates the presence of a high surface concentration of chlorophyll ${\underline{a}}$ against a scattering background. The index is high in 'red tide' conditions (intense, visible, surface, plankton blooms), and is also raised when aquatic vegetation is present. A bloom search based on MCI has resulted in detection of a variety of events in Canadian, Antarctic and other waters round the world, as well as detection of extensive areas of pelagic vegetation (Sargassum spp.), previously unreported in the scientific literature. Since June 1 2006, global MCI composite images, at a spatial resolution of 5 km, are being produced daily from all MERIS (daylight) passes of Reduced Resolution (RR) data. The global composites significantly increase the area now being searched for events, though the reduced spatial resolution may cause smaller events to be missed. This paper describes the composites and gives examples of plankton bloom events that they have detected. It also shows how the composites show the effect of the South Atlantic Anomaly, where cosmic rays affect the MERIS instrument.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.131-134
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• 2007

In this paper, we evaluate a red tide detection possibility of GOCI(Geostationary Ocean Color Imager) which will be launched in 2008. To detect red tide, we use a similar wavelength range of MODIS normalized water-leaving radiance data instead of GOCI data. Supposed to GOCI, red tide detection algorithm is based on MRI(MODIS Red tide Index) and use 667nm band to filter turbid water. The algorithm's effectiveness is verified by detecting large Cochlodinium polykrikoides red tide event that was appeared in Korean coastal waters. The evaluation was done by comparing the result with the update data provided by the NFRDI.