• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.573-577
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• 2002

The Landsat Program is the longest running enterprise for acquisition of imagery of the Earth from space. The first Landsat satellite was launched in 1972 and the most recent, Landsat 7, was launched on April 15, 1999. The Landsat satellites have acquired millions of images. The Landsat 7 receiving station is installed at more than 25 sites and will be installed in Korea. This paper will address the work being carried out for the development of image receiving and processing system for the Landsat 7 image data, which will be used at ground station of Landsat 7 in Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.313-321
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• 2002

Supplying high-resolution satellite image, we take much interest in the update and the revision of digital map and thematic map based on the satellite image. This study presented the possibility of the update and the revision to the existing digital map on a scale of l/5,000 and 1/25,000 to take advantage of the IKONOS satellite image. We performed geometric correction to make use of the ground control points of the existing digital map in IKONOS mono-image and created ortho-image by extracting digital elevation model from three dimensional contour data and altitude on the existing digital map. We revised changed features in the method of screen digitizing by overlapping orthorectified satellite image and existing digital map and flawed features of the unchanged area on the satellite images for positional accuracy analysis. As a result, rectification error is calculated at $\pm$3.35m by RMSE. There is a good possibility of update of digital map under the scale of 1/10,000. It is possible to the update of the large scale digital map over the scale of l/5,000, as if we used the method of stereo image and ground control point surveying.

• Smart Media Journal
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• v.11 no.1
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• pp.17-30
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• 2022

Like other computer vision research trends, research using satellite images was able to achieve rapid growth with the development of GPU-based computer computing capabilities and deep learning methodologies related to image processing. As a result, satellite images are being used in various fields, and the number of studies on how to use satellite images is increasing. Therefore, in this paper, we will introduce the field of research and utilization of satellite images and datasets that can be used for research using satellite images. First, studies using satellite images were collected and classified according to the research method. It was largely classified into a Regression-based Approach and a Classification-based Approach, and the papers used by other methods were summarized. Next, the datasets used in studies using satellite images were summarized. This study proposes information on datasets and methods of use in research. In addition, it introduces how to organize and utilize domestic satellite image datasets that were recently opened by AI hub. In addition, I would like to briefly examine the limitations of satellite image-related research and future trends.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.197-201
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• 2002

The high prices of satellite images prevent researchers from studying remote sensing and most non-professional people doesn't have the simple and easy solutions for the manipulation of satellite images. "Integrated Management of Satellite Imagery Information" project which will be promoted by ETRI (Electronics and Telecommunications Research Institute) will provide the solutions for the above mentioned problems. We will introduce the archiving center in this study. This includes the data construction, storage, management and distribution. We first review the background for this archiving center and introduce the interior and foreign institutes which archive and distribute satellite images. We review our H/W system and S/W system briefly. Finally, the further service of our project will be suggested. Since we will distribute the satellite images (Landsat, SPOT, JERS, Corona, Kompast-1) and will receive Landsat7 ETM+ in 2003 you, this will help the professional work dealing with the satellite image and attract the non-professional people for simple and easy manipulation solutions of satellite image.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.5
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• pp.253-259
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• 2018

Recently, small satellite industries are rapidly changing. Demand for high performance small satellites is increasing with the expansion of Earth Observation Satellite market. A next-generation small satellites require a higher resolution image storage capacity than before. However, there is a problem that the HW configuration of the existing small satellite image storage device could not meet these requirements. The conventional data storing system uses SDRAM to store image data taken from satellites. When SDRAM is used in small satellite platform of a next generation, there is a problem that the cost of physical space is eight times higher and satellite price is two times higher than NAND Flash. Using the same satellite hardware configuration for next-generation satellites will increase the satellite volume to meet hardware requirements. Additional cost is required for structural design, environmental testing, and satellite launch due to increasing volume. Therefore, in order to construct a low-cost, high-efficiency system. This paper shows a next-generation solid state recorder unit (SSRU) using MRAM and NAND Flash instead of SDRAM. As a result of this research, next generation small satellite retain a storage size and weight and improves the data storage space by 15 times and the storage speed by 4.5 times compare to conventional design. Also reduced energy consumption by 96% compared to SDRAM based storage devices.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.3
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• pp.181-188
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• 2012

Despite the ecological importance of seagrass beds, their distributional information in Korean coastal waters is insufficient. Therefore, we used hydroacoustic system to collect accurate bathymetry and classification of seagrass, and Kompsat-2 (4 m spatial resolution) image for detection of seagrass beds at Deukryang Bay, Korea. The accuracy of Kompsat-2 image classification was evaluated using hydracoustic survey result using error matrix and Kappa value. The total area of seagrass beds from satellite image classification was underestimated compared to the hydroacoustic survey, estimated 3.9 and $4.5km^2$ from satellite image and hydroacoustic data, respectively. Nonetheless, the accuracy of Kompsat-2 image classification over hydroacoustic-based method showing 90% (Kappa=0.85) for the three class maps (seagrass, unvegetated seawater and aquaculture). The agreement between the satellite image classification and the hydroacoustic result was 77.1% (the seagrass presence/absence map). From our result of satellite image classification, Kompsat-2 image is suitable for mapping seagrass beds with high accuracy and non-destructive method. For more accurate information, more researches with a variety of high-resolution satellite image will be preceded.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.100-102
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• 2003

This system is capable of obtaining quantitative information from images using natural features on the ortho-image maps that correspond with those from topographical maps. However, the qualitative information can also be obtained because because of the excellent visibility of ortho-image maps. There are plenty of promise for the use of ortho-image maps in the next generation topographic technology because of its wider applicability within the field. In keeping with the cutting edge, we produced ortho-image maps by scanning a specified area in narrow sections using the PKNU 2: a multispectral digital aerial photographing system made by ourselves. We evaluated the precision of the ortho-image maps, and performed an evaluation of the PKNU 2 system's capacity to improve the equipment of the PKNU 2. Ortho-image maps were made using Ground Control Points (GCPs) which were obtained from digital maps and aerial photographs of the PKNU 2. Thus, we demonstrated that it was possible to produce the ortho-image maps, which has a good constant level rate of less than 1m. The PKNU 2 system needs to be improving in the sensitivity of level maintenance equipment in the evaluation in terms of performance. It is thus required to survey the GCPs precisely for an accurate study.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.433-438
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• 1999

The land use type of Korea is high-density. So, the image classification using coarse resolution satellite image may not provide land cover classification results as good as expected. The purpose of this paper is to compare the result of visual interpretation with that of digital image classification of 20 m resolution SPOT satellite image at Kwangju-eup, Kyunggi-do, Korea. Classes are forest, cultivated field, pasture, water and residential area, which are clearly discriminated in visual interpretation. Maximum likelihood classifier was used for digital image classification. Accuracy assessment was done by comparing each classification result with ground truth data obtained from field checking. The classification result from the visual interpretation presented an total accuracy 9.23 percent higher than that of the digital image classification. This proves the importance of visual interpretation for the area with high density land use like the study site in Korea.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.415-424
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• 2006

In this paper, requirements of Meteorological Administration about Meteorological Image. (MI) of Communications, Ocean and Meteorological Satellite (COMS) is analyzed for the design of COMS ground station and according to the analysis results, the distribution image size of each observation area suitable for satellite Field Of View (FOV) stated at the requirements of meteorological administration is determined and the precise satellite FOV and the size of distribution image is calculated on the basis of the image size of the determined observation area. The results in this paper were applied to the detailed design for COMS ground station and also are expected to be used for the future observation scheduling and the scheduling of distribution of user data.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.1-9
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• 2011

The Communication Ocean and Meteorological Satellite(COMS), the first geostationary observation satellite, was successfully launched on June 27th in 2010. The raw data of Meteorological Imager(MI) and Geostationary Ocean Color Imager(GOCI), the main payloads of COMS, is delivered to end-users through the on-ground processing. The COMS Image Data Acquisition and Control System(IDACS) developed by Korea Aerospace Research Institute(KARI) in domestic technologies performs radiometric and geometric corrections to raw data and disseminates pre-processed image data and additional data to end-users through the satellite. Currently the IDACS is in the nominal operations phase after successful in-orbit testing and operates in National Meteorological Satellite Center, Korea Ocean Satellite Center, and Satellite Operations Center, During the in-orbit test period, validations on functionalities and performance IDACS were divided into 1) image data acquisition and transmission, 2) preprocessing of MI and GOCI raw data, and 3) end-user dissemination. This paper presents that IDACS' operational validation results performed during the in-orbit test period after COMS' launch.