• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.277-285
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• 2012

The GOCI imagery can be an effective alternative to monitor short-term changes over terrestrial environments. This study aimed to assess the radiometric characteristics of the GOCI multispectral imagery for land applications. As an initial approach, we compared GOCI at-sensor radiance with MODIS data obtained simultaneously. Dynamic range of GOCI radiance was larger than MODIS over land area. Further, the at-sensor radiance over various land surface targets were tested by vicarious calibration. Surface reflectance were directly measured in field using a portable spectrometer and indirectly derived from the atmospherically corrected MODIS product over relatively homogeneous sites of desert, tidal flat, bare soil, and fallow crop fields. The GOCI radiance values were then simulated by radiative transfer model (6S). In overall, simulated radiance were very similar to the actual radiance extracted from GOCI data. Normalized difference vegetation index (NDVI) calculated from the GOCI bands 5 and 8 shows very close relationship with MODIS NDVI. In this study, the GOCI imagery has shown appropriate radiometric quality to be used for various land applications. Further works are needed to derive surface reflectance over land area after atmospheric correction.

• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.65-71
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• 2015

Red Tide phenomenon which happens in the southern coast of Korea gives massive damage to the fishermen who run fish farms and thereby a lot of efforts to prevent damage are made from various angles. In particular, red tide monitoring with satellite imagery can make it possible to obtain the occurrence data of red tide throughout the whole areas of the sea, which helps provide important information for establishing the preventive plans of disasters. In this regard, this study selected the South Sea of Gyeongnam Province with a view to suggesting the monitoring results with regard to the spread and reduction of the Red Tide in the middle of the day by using the GOCI Images of COMS. With this intention, it selected the region in the South Sea of Gyeongnam Province. The study results of analysis on the GOCI image data for the years of 2013(Aug. 12) and 2014 (Sep. 11) are as follows: the pattern of the Red Tide in the region of the South Sea occurred in the southern sea area of Geoje-do in the morning. It gradually spread and showed a gradual decline after reaching the top at 1 PM. In addition, in terms of the tide movement in the middle of the day, Red Tide began in the southern sea area and moved to the west, and moved to the east again at noon. It is judged that additional study on many factors such as the characteristics of the future Red-tide organisms, tidal currents, amount of sunshine, and water temperature is needed, but it is estimated that Red Tide movement monitoring with GOCI images would provide very crucial information for predicting the spread and movement of the Red Tide to protect and manage the Red Tide disasters.

• Korean Journal of Remote Sensing
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• v.32 no.1
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• pp.25-38
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• 2016

With the increasing need for high temporal resolution satellite imagery for monitoring land surfaces, this study evaluated the temporal resolution of the NDVI composites from Geostationary Ocean Color Imager (GOCI) data. The GOCI is the first geostationary satellite sensor designed to provide continuous images over a $2,500{\times}2,500km^2$ area of the northeast Asian region with relatively high spatial resolution of 500 m. We used total 2,944 hourly images of the GOCI level 1B radiance data obtained during the one-year period from April 2011 to March 2012. A daily NDVI composite was produced by maximum value compositing of eight hourly images captured during day-time. Further NDVI composites were created with different compositing periods ranging from two to five days. The cloud coverage of each composite was estimated by the cloud detection method developed in study and then compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud product and 16-day NDVI composite. The GOCI NDVI composites showed much higher temporal resolution with less cloud coverage than the MODIS NDVI products. The average of cloud coverage for the five-day GOCI composites during the one year was only 2.5%, which is a significant improvement compared to the 8.9%~19.3% cloud coverage in the MODIS 16-day NDVI composites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.353-361
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• 2015

The area of red tides occurences, which brings enormous damages every year, have been expanded to the coastal waters across the nation. Regarding to this trend, the development of red tide detection technology by using the GOCI (Geostationary Ocean Color Imager) of COMS lauched in 2010 has been drawn attentions of researchers. This study purposed on analyzing the frequency and density of red tides occurence by using the GOCI for detecting the southern sea, whereas targeted area. The observation has brought over the last three years (2012, 2013, and 2014) before the analysis was conducted. Followingly, the study could be resulted in extracting and revealing the hot spots of the red tides from two of analysis in the overlay and density. The distribution patterns of red tide occurrences according to those observed years has been shown in irregular characteristics and various changes. However, the analysis of hot spots, based on the frequency of the red tide occurrence, has revealed that the frequency of red tide occurences is continuously increased in the specific sea area. Therefore, it is concluded in that the continuous monitoring can contribute to predict accurate movements of red tides, so as establish systematic plans for preventing disasters.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.129-136
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• 2014

This study deals with red tide detection by using the remote sensing imagery from the Geostationary Ocean Color Imager (GOCI), the world's first geostationary orbit satellite, around the southern coast of Korea where the most severe red tide occurred recently. The red tide zone was determined by the available data selection from the GOCI imagery during the period of red tide occurrence and also the severe red tide zone was detected through the spatial analysis by temporal change out of the red tide zone. This study results showed that the coast in the vicinity of the Hansan and Yokji in Tongyeong-si was classified into the severe red tide zone, and that the red tide was likely to spread from the coast of Hansan and Yokji to the one of Sanyang-eub. In addition, the comparative analysis between the area of red tide occurrence, the prevention activities of Gyeongsangnam-do provincial government and the amount of the damage cost over time showed close correlation among them. It is still early to conclude that the study is showing the severe red tide zone and the spread path exactly due to various factors for red tide occurrence and activities. In order to improve the reliability of the results, the more data analysis is required.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.