• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.49-52
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• 2007

This study uses empirical method to estimate absorption coefficient of colored dissolved organic matter $(a_{dom})$ from GOCI satellite data with the relationship between band ratio of remote sensing reflectance $(R_{rs})$ and $a_{dom}$. For development of $a_{dom}$ estimation algorithm, the used data is in-situ data about ocean optical properties in the around seawater area of the Korean Peninsula during 1998 - 2005. The relationship of $R_{rs}$(412)/$R_{rs}$(555), $R_{rs}$(443)/$R_{rs}$(555), $R_{rs}$(490)/$R_{rs}$(555), $R_{rs}$(510)/$R_{rs}$(555) and $a_{dom}$(412) showed $R^2$ values of 0.707, 0.707, 0.597 and 0.552, respectively. The spectrum of $a_{dom}({\lambda})$ is shape of exponential function $a_{dom}({\lambda})$ value decreases with increasing wavelength. For estimation of $a_{dom}$ from satellite data, we developed an algorithm from the relationship of $a_{dom}$(412) and $R_{rs}$(412)/$R_{rs}$(555). This algorithm was employed on SeaWiFS imagery to estimate $R_{rs}$(412) in the South Sea, East Sea, Yellow Sea and northern East China Sea areas. Also, SeaDAS-derived $a_{dg}$(412) from same SeaWiFS imagery, These $a_{dg}$(412) was then compared with in-situ and empirical-algorithm-derived $a_{dom}$(412), but these values were different. We think two points that such different values are caused by discrepancy related to failure of standard atmospheric correction scheme, the other are caused by error related to definition of $a_{dom}$(412) and $a_{dg}$(412).

• 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.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.175-188
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• 2010

A new correction method is required for the Geostationary Ocean Color Imager (GOCI), which is the world's first ocean color observing sensor in geostationary orbit. In this paper we introduce a new method of atmospheric and the Bidirectional Reflectance Distribution Function(BRDF) correction for GOCI. The Spectral Shape Matching Method(SSMM) and the Sun Glint Correction Algorithm(SGCA) were developed for atmospheric correction, and BRDF correction was improved using Inherent Optical Property(IOP) data. Each method was applied to the Sea-Viewing Wide Field-of-view Sensor(SeaWiFS) images obtained in the Korean sea area. More accurate estimates of chlorophyll concentrations could be possible in the turbid coastal waters as well as areas severely affected by aerosols.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.157-165
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• 2010

In June 2010, Geostationary Ocean Color Imager (GOCI), the world's first ocean color observation satellite will be launched. GOCI is planned for use in real-time monitoring of the ocean environment around Korean Peninsula by daily analysis of ocean environment measurements of chlorophyll concentration, dissolved organic matter, and suspended sediments taken eight times per day for seven years. GOCI primary data will support a fishery information service and red tide forecasting, and ocean climate change research. In this paper, the development background of GOCI, user requirements, GOCI architecture, and the GOCI on-orbit operational concept are explained.

• Proceedings of the KSRS Conference
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• v.1
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• pp.491-494
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• 2006

The west coast of Northern Borneo is strongly influenced by Asian monsoon. Present research using the satellite ocean color (OC) remote sensing has identified some interesting oceanographic phenomena in this area that could be related to the harmful algal blooms (HAB). Occurrence of seasonal upwelling event was noticed off the northern tip of Borneo Island that could be related to the northeast monsoon wind. Harmful algal blooms by Pyrodinium bahamense var. compressum occurred since 1976. Subsequently, during December 2003, there was a report of new HAB by Cochlodinium polykrikoides in Northern Borneo. Analysis of OC images revealed that the Cochlodinium bloom had very high chlorophyll a signal and strong absorption characteristics. Results showed that the Baram River plume and upwelling at Northern Borneo were the source of nutrient for the Cochlodinium bloom in the offshore region. Ocean color images of 2004 showed that the bloom from Northern Borneo had crossed the Balabac Straits, reaching Palawan Island in Philippine. Due to the possibility of transboundary HAB problem, we propose a regional HAB monitoring network for an effective HAB management.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.366-375
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• 1998

Optical characteristics of the yellow sand and their influences on the ocean color remote sensing has been studied using ocean color sensor SeaWiFS measurements. Two cases of April 18 and April 25, 1998, representing yellow sand and background aerosol, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. Optical thickness of yellow sand arrived over the East Asian sea waters in April 18 indicates that there are two groups loaded with relatively homogeneous yellow sand, i.e.: heavy yellow sand area with optical thickness peak around 0.8 and mild area with about 0.4, which are consistent with ground observations. The movement of the yellow sand area obtained from surface weather maps and backward trajectory analysis manifest the notion that the weak yellow sand area was originated from the outer region of the dust storm. It is also noted that high optical thickness associated with the yellow sand is significantly different from what we may observe from background aerosol, which is about 0.2. These characteristics allow us to determine the yellow sand area with an aid of atmospheric correction parameter. Results indicate that the yellow sand area can be determined by applying the features revealed in scattergrams of atmospheric correction parameter and optical thickness.

• 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.

• Proceedings of the KSRS Conference
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• v.1
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• pp.290-293
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• 2006

COMS (Communication, Ocean and Meteorological Satellite) shall be operated with two remote sensing payloads, MI (Meteorological Imager) and GOCI (Geostationary Ocean Color Imager). Since both payloads have rotating mechanisms, the dynamic coupling between two payloads is very important considering the pointing stability during GOCI operation. In addition, COMS adopts a single solar wing to improve the image quality, which leads to the unbalanced solar pressure torque in COMS. As a result, the off-loading of the wheel momentum needs to be performed regularly (2 times per day). Since the frequent off-loading could affect MI/GOCI imaging performance, another suboptimal off-loading time needs to be considered to meet the AOCS design requirements of COMS while having margin enough in the number of thruster actuations. In this paper, preliminary analysis results on the pointing stability and the wheel off-loading time selection with respect to MI/GOCI operations are presented.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.390-395
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• 1999

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring for the study of biological oceanography KOMPSAT will be launched in the middle of November this year. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance measurement data for 8 primary spectral bands of OSMI. The radiometric response linearity and dynamic range are analyzed for the image radiometric calibration and the estimation of OSMI image quality for the ocean remote sensing area. The dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.135-143
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• 2000

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-Purpose SATellite (KOMPSAT) to perform global ocean color monitoring for the study of biological oceanography. HOMPSAT was launched 21 December 1999. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance data measured before launch. The radiometric response linearity and dynamic range are analyzed and the dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.