• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.277-285
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• 2010

Geostationary Ocean Color Imager(GOCI-I), the world's first space-borne ocean color observation geostationary satellite, will be launched on June 2010. Development of GOCI-I took about 6 years, and its expected lifetime is about 7 years. The mission and user requirements of GOCI-II are required to be defined at this moment. Because baseline of the main mission of GOCI-II must be defined during the development time and early operational period of GOCI-I. The main difference between these missions is the global-monitoring capability of GOCI-II, which will meet the necessity of the monitoring and research on climate change in the long-term. The user requirements of GOCI-II will have higher spatial resolution, $250m{\times}250m$, and 12 spectral bands to fulfill GOCI-I's user request, which could not be implemented on GOCI-I for technical reasons. A dedicated panchromatic band will be added for the nighttime observation to obtain fishery information. GOCI-II will have a new capability, supporting user-definable observation requests such as clear sky area without clouds and special-event areas, etc. This will enable higher applicability of GOCI-II products. GOCI-II will perform observations 8 times daily, the same as GOCI-I's. Additionally, daily global observation once or twice daily is planned for GOCI-II. In this paper, we present an improved development and organization structure to solve the problems that have emerged so far. The hardware design of the GOCI-II will proceed in conjunction with domestic or foreign space agencies.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.137-144
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• 2007

In KORDI (Korea Ocean Research and Development Institute), the KOSC (Korea Ocean Satellite Center) construction project is being prepared for acquisition, processing and distribution of sensor data via L-band from GOCI (Geostationary Ocean Color Imager) instrument which is loaded on COMS (Communication, Ocean and Meteorological Satellite); it will be launched in 2008. Ansan (the headquarter of KORDI) has been selected for the location of KOSC between 5 proposed sites, because it has the best condition to receive radio wave. The data acquisition system is classified into antenna and RF. Antenna is designed to be $\phi$ 9m cassegrain antenna which has 19.35 G/T$(dB/^{\circ}K)$ at 1.67GHz. RF module is divided into LNA (low noise amplifier) and down converter, those are designed to send only horizontal polarization to modem. The existing building is re-designed and arranged for the KOSC operation concept; computing room, board of electricity, data processing room, operation room. Hardware and network facilities have been designed to adapt for efficiency of each functions. The distribution system which is one of the most important systems will be constructed mainly on the internet. and it is also being considered constructing outer data distribution system as a web hosting service for offering received data to user less than an hour.

• 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.34 no.6_2
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• pp.1203-1213
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• 2018

In Arctic and Antarctic ocean, remote sensing is the most effective observation for environmental changes due to the inaccessibility of the regions. Even though satellite, UAV (Unmanned Aerial Vehical) are well known remote sensing platforms, and research vessel also used for automatic measurement on the regions, varied environment of Polar regions require time series and wide coverage of data. Especially, in high latitude, apply an optical satellite remote sensing is not easy due to low sun altitude. In this paper, we introduce an operation of hyper-spectrometer (HyperSAS/Satlantic inc.) which is mounted on Ice Breaker Research Vessel ARAON of Korea Polar Research Institute since 2010, to acquire an above water reflectance atomatically through every research cruise on Arctic and Antarctic ocean and transit both regions. In addition to, auxiliary data for the remotely acquired data, in situ water sampling were also obtained. The above water reflectance and in situ water sampling data are continuously acquired since 2010 will contribute to improve an Ocean Color algorithm in the high latitude and help to understand ocean reflectances over from high latitude through low latitude. Preliminary result from above water reflectance showed characteristics of Arctic ocean and Antarctic Ocean and used to develop algorithms for estimating various ocean factors such as chlorophyll and suspended sediment.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1089-1098
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• 2020

In this study, we propose a method to detect red tide Cochlodinium Polykrikoide using by machine learning and geostationary marine satellite images. To learn the machine learning model, GOCI Level 2 data were used, and the red tide location data of the National Fisheries Research and Development Institute was used. The machine learning model used logistic regression model, decision tree model, and random forest model. As a result of the performance evaluation, compared to the traditional GOCI image-based red tide detection algorithm without machine learning (Son et al., 2012) (75%), it was confirmed that the accuracy was improved by about 13~22%p (88~98%). In addition, as a result of comparing and analyzing the detection performance between machine learning models, the random forest model (98%) showed the highest detection accuracy.It is believed that this machine learning-based red tide detection algorithm can be used to detect red tide early in the future and track and monitor its movement and spread.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1541-1551
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• 2023

Radiometric calibration is a fundamental step in ocean color remote sensing since the step to derive solar radiance spectrum in visible to near-infrared wavelengths from the sensor-observed electromagnetic signals. Generally, satellite sensor suffers from degradation over the mission period, which results in biases/uncertainties in radiometric calibration and the final ocean products such as water-leaving radiance, chlorophyll-a concentration, and colored dissolved organic matter. Therefore, the importance of radiometric calibration for the continuity of ocean color satellites has been emphasized internationally. This study introduces an approach to improve the radiometric calibration algorithm for the visible bands of the Geostationary Ocean Color Imager-II (GOCI-II) satellite with a focus on stability. Solar Diffuser (SD) measurements were employed as an on-orbit radiometric calibration reference, to obtain the continuous monitoring of absolute gain values. Time series analysis of GOCI-II absolute gains revealed seasonal variations depending on the azimuth angle, as well as long-term trends by possible sensor degradation effects. To resolve the complexities in gain variability, an azimuth angle correction model was developed to eliminate seasonal periodicity, and a sensor degradation correction model was applied to estimate nonlinear trends in the absolute gain parameters. The results demonstrate the effects of the azimuth angle correction and sensor degradation correction model on the spectrum of Top of Atmosphere (TOA) radiance, confirming the capability for improving the long-term stability of GOCI-II data.

• Journal of computational fluids engineering
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• v.15 no.2
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• pp.28-34
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• 2010

Conductive and radiative thermal model configurations of an imager of a geostationary satellite are presented. A two-plane method is introduced for three dimensional conductive coupling which is not able to be treated by thin shell plate thermal modeling technique. Especially the two-plane method is applied to massive matters and PIP(Payload Interface Plate) in the imager model. Some massive matters in the thermal model are modified by adequate correction factors or equivalent thickness in order to obtain the numerical results of thermal modeling to be consistent with the analytic model. More detailed nodal breakdown is specially employed to the object which has the rapid temperature gradient expected by a rule of thumb. This detailed thermal model of the imager is supposed to be used for analyses and test predictions, and be correlated with the thermal vacuum test results before final in-flight predictions.

• Current Industrial and Technological Trends in Aerospace
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• v.8 no.2
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• pp.65-75
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• 2010

In 2014, Japan is scheduled to launch GCOM(Global Change Observation Mission)-C for the global change observation mission, where SGLI(Second-generation Global Imager) is planned for optical multi-channel observation ofa radiation budget and a carbon cycle. Depending on the spectral channels, SGLI consists ofS GLI-VNR(Visible Near IR) and SGLI-IRS(IR Scanning). Their main design schemes are mostly based upon those ofthe previous instruments ever developed in Japan, which is intended to reduce the development risk for the advanced performance. Accordingly, for the better understanding ofSG LI, the paper reviews the history oft he Japanese optical payloads from two different views: VNR and IR. Through the review, a comparison among the Japanese optical instruments is made to distinguish the development trend toward SGLI ofGC OM-C.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.2
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• pp.38-45
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• 2001

Three lines from $36_{\circ}$ N, $124_{\circ}$ E, and $132_{\circ}$ E of the East Sea and the Yellow Sea were chosen to extract spectra of normalized water leaving radiances. Comparative analysis of the OCTS algorithm and SeaWiFS(OC-2) algorithms was presented here. OCTS algorithm have more overestimate than SeaWiFS(OC-2 algorithm) for detecting chlorophyll concentration. Atmospheric correction algorithm that is excluded the effect of SS in the case 2 water need for long term ocean environmental monitoring of the East Sea and the Yellow Sea. And, considered the effect of CDOM and SS, bio-optical algorithm have to be developed in this research.

• Journal of the Korean Society for Marine Environment & Energy
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• v.5 no.4
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• pp.19-26
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• 2002

This is a brief report on the development of a system which provides fishing vessels with a real-time key information that can direct to regions of high fish density. Water temperature and Plankton distribution are the base parameters and various public information have been examined and summarized. The suface water temperature can be obtained from NOAA's high resolution infrared data base and the vertical water temperature can be obtained from TAO/TRITON's buoy near the equator and ARGOS's drifting buoy covering wider Pacific ocean. MODIS's data is also utilized for sea color information. A model data format is proposed and a few examples are demonstrated.