• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.154-162
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• 2011

The KOrea Multi-Purpose Satellite-3 (KOMPSAT-3) provides 0.7 m Ground Sample Distance (GSD) panchromatic image and 2.8 m GSD multi-spectral image data for various applications. The KOMPSAT-3 system data will be applied in the field of earth observations, covering land, sea, coastal zones, and Geographic Information Systems (GIS). In order to keep the swath width of 15km at nadir view of KOMPSAT-3, CCD consist of approximately 24,020 pixels excluding 20 dark pixels at both sides and has overlap region. Because there are no CCD-line sensors with a pixel size of $7{\mu}m$, the field of view is separated into 2 parts and imaged on 2 detectors, each with 12,080 pixels. Therefore, 2 detectors have different geometric characteristic. This paper provides image simulation for geometric characteristics analysis of overlapping area of KOMPSAT-3 using KOMPSAT-2 image data.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.53-57
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• 2003

As the Korea Multi-Purpose Satellite-I (KOMPSAT-1) satellite can roll tilt up to $\pm$45$^{\circ}$, we have analyzed some KOMPSAT-1 EOC images taken at different tilt angles for this study. The required ground coordinates for bundle adjustment and geometric accuracy are obtained from the digital map produced by the National Geography Institution, at a scale of 1:5,000. Followings are the steps taken for the tilting angle of KOMPSAT-1 to be present in the evaluation of geometric accuracy of each different stereo image data: Firstly, as the tilting angle is different in each image, the characteristic of satellite dynamic must be determined by the sensor modeling. Then the best sensor modeling equation should be determined. The result of this research, the difference between the RMSE values of individual stereo images is mainly due to quality of image and ground coordinates instead of tilt angle. The bundle adjustment using three KOMPSAT-1 stereo pairs, first degree of polynomials for modeling the satellite position, were sufficient.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.157-164
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• 2011

As high-resolution satellite images have enabled large scale topographic mapping and monitoring on global scale with short revisit time, agile sensor orientation, and large swath width, many countries make effort to secure the satellite image information. In Korea, KOMPSAT-2 (KOrea Multi-Purpose SATellite-2) was launched in July 28 2006 with high specification. These satellites have stereo image acquisition capability for 3D mapping and monitoring. To efficiently handle stereo images such as stereo display and monitoring, the accurate epipolar image generation process is prerequisite. However, the process was highly limited due to complexity in epipolar geometry of pushbroom sensor. Recently, the piecewise approach to generate epipolar images using RPC was developed and tested for in-track IKONOS stereo images. In this paper, the piecewise approach was tested for KOMPSAT-2 across-track stereo images to see how accurately KOMPSAT-2 epipolar images can be generated for 3D geospatial applications. In the experiment, two across-track stereo sets from three KOMPSAT-2 images of different dates were tested using RPC as the sensor model. The test results showed that one-pixel level of y-parallax was achieved for manually measured tie points.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.47-55
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• 2002

Remote sensing is the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation./sup 1)/ EOC (Electro -Optical Camera) sensor loaded on the KOMPSAT-1 (Korea Multi- Purpose Satellite-1) performs the earth remote sensing operation. EOC can get high-resolution images of ground distance 6.6m during photographing; it is possible to get a tilt image by tilting satellite body up to 45 degrees at maximum. Accordingly, the device developed in this study enables to obtain images by photographing one pair of tilt image for the same point from two different planes. KOMPSAT-1 aims to obtain a Korean map with a scale of 1:25,000 with high resolution. The KOMPSAT-1 developed automated feature extraction system based on stereo satellite image. It overcomes the limitations of sensor and difficulties associated with preprocessing quite effectively. In case of using 6, 7 and 9 ground control points, which are evenly spread in image, with 95% of reliability for horizontal and vertical position, 3-dimensional positioning was available with accuracy of 6.0752m and 9.8274m. Therefore, less than l0m of design accuracy in KOMPSAT-1 was achieved. Also the ground position error of ortho-image, with reliability of 95%, is 17.568m. And elevation error showing 36.82m was enhanced. The reason why elevation accuracy was not good compared with the positioning accuracy used stereo image was analyzed as a problem of image matching system. Ortho-image system is advantageous if accurate altitude and production of digital elevation model are desired. The Korean map drawn on a scale of 1: 25,000 by using the new technique of KOMPSAT-1 EOC image adopted in the present study produces accurate result compared to existing mapping techniques involving high costs with less efficiency.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.35-45
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• 2010

The objective of this study is to verify the positional accuracy by performing the orthometric corrections on the high resolution satellite images and to analyze the band correlation between the high resolution images corrected with orthometric correction. The objectives also included an analysis on the correlation of NDVI. For the orthometric correction of images from KOMPSAT2 and IKONOS, systematic errors were removed in use of RPC data, and non-planar distortions were corrected with GPS surveying data. Also, by preempting the image points at the same positions within ortho images, a comparison was performed on positional accuracies between image points of each image and GPS surveying points. The comparison was also made on the positional accuracies of image points. between the images. For correlation of band and correlation of NDVI, the descriptive statistics of DN values were acquired for respective bands by adding the Quickbird images and Aerial Photographs undergone through orthometric correction at the time of purchase. As result, from a comparison on positional accuracies of Orthoimages from KOMPSAT2 and Ortho Images of IKONOS was made. From the comparison the distance between the image points within each image and GPS surveying points was identified as 3.41m for KOMPSAT2 and as 1.45m for IKONOS, presenting a difference of 1.96m. Whereas, RMSE between image points was identified as 1.88m. The level of correlation was measured by using Quickbird, KOMPSAT2, IKONOS and Aerial Photographs between inter-image bands and NDVI, showing that there were high levels of correlation between Quickbird and IKONOS identified from all bands as well as from NDVI, except a high level of correlation that was identified between the Aerial Photographs and KOMPSAT2 from Band 2. Low levels of correlation were also identified between Quickbird and Aerial Photographs from Band 1. and between KOMPSAT2 and IKONOS from Band 2 and Band 4, whereas, KOMPSAT2 showed low correlations with Aerial Photographs from Band 3. For NDVI, KOMPSAT2 showed low level of correlations with both of QuickBird and IKONOS.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.565-578
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• 2018

In this paper, we investigate the feasibility of modelling image strips, instead of individual scenes, that have been acquired from the same orbital pass through the process of bundle adjustments. Under this approach, First, a rational function model (RFM) of the strip image is generated from the RFMs of individual images, such that the entire strip of images can be treated as a single image. Correction parameters are calculated through bundle adjustments between strip images. For the experiment, we used two stereo strips. Each strip image consists of three KOMPSAT-3A scenes. Experimental results show that it was possible to improve the initial model by using the control points located in a specific region of the strip. We showed that absolute orientation with moderate accuracy of 2 m errors were achieved from 12 ground control points for the three-image strips. The test results indicate that bundle adjustment of strip images could be more efficient than bundle adjustments of the individual scenes.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1223-1232
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• 2017

This paper presents an approach to detect changes caused by urban development over a large area using KOMPSAT optical images. In order to minimize the radiometric dissimilarities between the images acquired at different times, we apply the grid-based rough radiometric correction as a preprocessing to detect changes in a large area. To improve the accuracy of the change detection results for urban development, we mask-out non-interest areas such as water and forest regions by the use of land-cover map provided by the Ministry of Environment. The Change Vector Analysis(CVA) technique is applied to detect changes caused by urban development. To confirm the effectiveness of the proposed approach, a total of three study sites from Sejong City is constructed by combining KOMPSAT-2 images acquired on May 2007 and May 2016 and a KOMPSAT-3 image acquired on March 2014. As a result of the change detection accuracy evaluation for the study site generated from the KOMPSAT-2 image acquired on May 2007 and the KOMPSAT-3 image acquired on March 2014, the overall accuracy of change detection was about 91.00%. It is demonstrated that the proposed method is able to effectively detect urban development changes in a large area.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.221-232
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• 2021

This study analyzed co-registration results according to the geometric processing level of reference image, which are Level 1R and Level 1G provided from KOMPSAT-3 and KOMPSAT-3A images. We performed co-registration using each Level 1R and Level 1G image as a reference image, and Level 1R image as a sensed image. For constructing the experimental dataset, seven Level 1R and 1G images of KOMPSAT-3 and KOMPSAT-3A acquired from Daejeon, South Korea, were used. To coarsely align the geometric position of the two images, SURF (Speeded-Up Robust Feature) and PC (Phase Correlation) methods were combined and then repeatedly applied to the overlapping region of the images. Then, we extracted tie-points using the SURF method from coarsely aligned images and performed fine co-registration through affine transformation and piecewise Linear transformation, respectively, constructed with the tie-points. As a result of the experiment, when Level 1G image was used as a reference image, a relatively large number of tie-points were extracted than Level 1R image. Also, in the case where the reference image is Level 1G image, the root mean square error of co-registration was 5 pixels less than the case of Level 1R image on average. We have shown from the experimental results that the co-registration performance can be affected by the geometric processing level related to the initial geometric relationship between the two images. Moreover, we confirmed that the better geometric quality of the reference image achieved the more stable co-registration performance.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.37-45
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• 2014

This paper reports the geolocation accuracy of KOMPSAT-3 imagery. KOMPSAT-3 was launched successfully on May 18, 2012 and has been released last March. In this paper, we have checked the geolocation accuracy of initial sensor model, precise sensor model and stereo-and multi-image model using four KOMPSAT-3 images covering the same area. The KOMPSAT-3 images without GCPs provided the geolocation accuracy of about 30m and the geocorrected KOMPSAT-3 images provided the geolocation accuracy of about 1m or less. KOMPSAT-3 stereo- and multi-images models yield threedimensional points with sub-meter accuracy in horizontal and vertical direction. Overall, KOMPSAT-3 showed much improved performance in terms of the geolocation accuracy over KOMPSAT-2. KOMPSAT-3 is expected to be able to replace foreign satellite data with sub-meter accuracy level for achieving accurate geometric information.