• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.196-201
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• 2009

KOMPSAT-2 위성영상은 공간해상도가 우수한 1-m급 전정색 영상과, 상대적으로 분광해상도가 우수한 4-m급 다중분광 영상을 동시 취득하는 다중 센서이다. 영상융합기법의 적용을 통해 1-m급 고해상도 다중분광 영상의 취득이 가능하며, 이것은 1-m급에서 식별 가능한 객체들을 분류하고 변화 탐지하는데 활용될 수 있다. 본 연구는 IHS (Intensity-Hue-Saturation) 융합 기법의 I (Intensity) 와 $\delta$ 값을 조정함으로써 새로운 융합기법을 제안하였으며, 육안분석과 상관계수를 가지고 다른 융합기법들과 비교분석하였다. 실험 결과, 제안된 기법의 융합영상은 원본 다중분광영상과 가장 높은 상관계수를 나타내었으며, 상관계수가 유사한 웨이브릿 융합 또는 고대역 필터링과의 육안분석에서 확연히 우수한 공간 선명도를 나타내는 것으로 평가되었다.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1537-1549
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• 2020

The ground sample distance of KOMPSAT-3 is 0.7 m for panchromatic band, 2.8 m for multi-spectral band, and the swath width of KOMPSAT-3 is 16 km. Therefore, an image of an area wider than the swath width (16 km) cannot be acquired with a single scanning. Thus, after scanning multiple areas in units of swath width, the acquired images should be made into one image. At this time, the necessary algorithm is called image mosaicking or image stitching, and is used for cartography. Mosaic algorithm generally consists of the following 4 steps: (1) Feature extraction and matching, (2) Radiometric balancing, (3) Seamline estimation, and (4) Image blending. In this paper, we have studied an effective seamline estimation method for satellite images. As a result, we can estimate the seamline more accurately than the existing method, and the heterogeneity of the mosaiced images was minimized.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.75-82
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• 2009

In order to help general users to analyze the KOMPSAT-2 data, an application of sensor modeling to commercial software was explained in this document. The sensor modeling is a basic step to extract the quantity and quality information from KOMPSAT-2 data. First, we introduced the contents and type of ancillary data offered with KOMPSAT-2 PAN image data, and explained how to use it with commercial software. And then, we applied the polynomial-base and refine RFM sensor modeling with ground control points. In the polynomial-base sensor modeling, the accuracy which is average RMSE of check points is highest when the satellite position was calculated by type of 1st order function and the satellite attitude was calculated by type of 1st order function for (Y axis), (Z axis) or constant for (X axis), (Y axis), (Z axis) in perspective center position and satellite attitude parameters. As a result of refine RFM sensor modeling, the accuracy is less than 1 pixel when we applied affine model..

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.99-107
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• 2014

There are two types of Physical Model and RFM (Rational Function Model) is to determinate ground coordinates using KOMPSAT-2 and KOMPSAT-3 satellite data. Generally, RPCs(Rational Polynomial Coefficients) based on RFM is provided for users. This RPCs is to compute the ground coordinates to the image coordinates. If users produce ortho-image with provided RPCs is useful, directly compute the ground coordinates corresponding to image coordinates and check location accuracy etc. are difficult. In this study, a basic algorithm of inverse RPCs that calculates the image coordinates to ground coordinates, compute based on provided RPCs and evaluation of determinated ground coordinates using developed inverse RPCs were proposed.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.21-35
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• 2009

KOMPSAT-2 is the seventh high-resolution image satellite in the world that provides both 1m-grade panchromatic images of the GSD and 4m-grade multispectral images of the GSD. It's anticipated to be used across many different areas including mapping, territory monitoring and environmental watch. However, due to the complexity and security concern involved with the use of the MSC, the use of KOMPSAT-2 images are limited in terms of geometric images, such as satellite orbits and detailed mapping information. Therefore, this study aims to produce DEM and orthoimage by using the stereo images of KOMPSAT-2, and to explore the applicability of geo-spatial information with KOMPSAT -2. Orientation interpretations were essential for the production of DEM and orthoimage using KOMPSAT-2 images. In the study, they are performed by utilizing both RPC and GCP. In this study, the orientation interpretations are followed by the generation of DEM and orthoimage, and the analysis of their accuracy based on a 1:5,000 digital map. The accuracy analysis of DEM is performed and the results indicate that their altitudes are, in general, higher than those obtained from the digital map. The altitude discrepancies on plains, hills and mountains are calculated as 1.8m, 7.2m, and 11.9m, respectively. In this study, the mean differences between horizontal position between the orthoimage data and the digital map data are found to be ${\pm}3.081m$, which is in the range of ${\pm}3.5m$, within the permitted limit of a 1:5,000 digital map. KOMPSAT-2 images are used to produce DEM and orthoimage in this research. The results suggest that DEM can be adequately used to produce digital maps under 1:5,000 scale.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.977-985
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• 2020

KOMPSAT-3A launched in 2015 provides Middle InfraRed(MIR) images with 3.3~5.2㎛. Though the satellite provide high resolution images for estimating bright temperature of ground objects, it is different from existing satellites developed for natural science purposes. An atmospheric compensation process is essential in order to estimate the surface brightness temperature from a single channel MIR image of KOMPSAT-3A. However, even after the atmospheric compensation process, there is a brightness temperature error due to various factors. In this paper, we analyzed the cause of the brightness temperature estimation error by tracking signal flow from camera physical characteristics to image processing. Also, we study on possibility of improvement of MIR brightness temperature bias error of KOMPSAT-3A using GEOKOMPSAT-2A. After bias compensation of a real nighttime image with a large bias error, it was confirmed that the surface brightness temperature of KOMPSAT-3A and GEOKOMPSAT-2A have correlation. We expect that the GEOKOMPSAT-2A images will be helpful to improve MIR brightness temperature bias error of KOMPSAT-3A.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.43-52
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• 2004

This study presents the application of aerial photographs and the Korea Multi-Purpose Satellite, KOMPSAT-1 Electro-Optical Camera(EOC) imagery in detecting change in an urban area that has been rapidly growing. For the study, we used multi-temporal images which were acquired by two different sensors. Image registration and resampling were rallied out before performing change detection in a common reference system with the same spatial resolution. for all of the images. Results from image differencing and image ratioing techniques show that panchromatic aerial photographs and KOMPSAT-1 EOC images collected by different sensors have potential to detect changes of urban features such as building, road and other man-made structure. And the optimal threshold values were suggested in applying image differencing and image ratioing techniques for change detection.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.63-71
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• 2013

This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.39-54
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• 2012

The objective of this study is to propose efficient data fusion techniques feasible to the KOMPSAT-2 satellite images. The most widely used image fusion techniques, which are the high-pass filter (HPF), the intensity-hue-saturation-based (modified IHS), the pan-sharpened, and the wavelet-based methods, was applied to four KOMPSAT - 2 satellite images having different regional and seasonal characteristics. Each fusion result was compared and analyzed in spatial and spectral features, respectively. Quality evaluation of image fusion techniques was performed in both quantitative and visual analysis. The quantitative analysis methods used for this study were the relative global dimensional error (spatial and spectral ERGAS), the spectral angle mapper index (SAM), and the image quality index (Q4). The results of quantitative and visual analysis indicate that the pan-sharpened method among the fusion methods used for this study relatively has the suitable balance between spectral and spatial information. In the case of the modified IHS method, the spatial information is well preserved, while the spectral information is distorted. And also the HPF and wavelet methods do not preserve the spectral information but the spatial information.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1605-1613
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• 2020

The tidal channel is a coastal sedimentary terrain that plays the most important role in the formation and development of tidal flats, and is considered a very important index for understanding and distribution of tidal flat sedimentation/erosion terrain. The purpose of this study is to understand the changes in tidal channels by a period after the opening of the floodgate of the seawall in the reclaimed land of Sihwa Lake using KOMPSAT high-resolution multispectral satellite image data and to evaluate the applicability and efficiency of high-resolution satellite images. KOMPSAT 2 and 3 images were used for extraction of the tidal channels' lineaments in 2009, 2014, and 2019 and were applied to supervised classification method based on Principal Component Analysis (PCA), Artificial Neural Net (ANN), Matched Filtering (MF), and Spectral Angle Mapper (SAM) and band ratio techniques using Normalized Difference Water Index (NDWI) and MF/SAM. For verification, a numerical map of the National Geographic Information Service and Landsat 7 ETM+ image data were utilized. As a result, KOMPSAT data showed great agreement with the verification data compared to the Landsat 7 images for detecting a direction and distribution pattern of the tidal channels. However, it has been confirmed that there will be limitations in identifying the distribution of tidal channels' density and providing meaningful information related to the development of the sedimentary process. This research is expected to present the possibility of utilizing KOMPSAT image-based high-resolution remote exploration as a way of responding to domestic intertidal environmental issues, and to be used as basic research for providing multi-platform-image-based convergent thematic maps and topics.