• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1523-1535
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• 2020

In order to produce crop information using remote sensing, we use classification and growth monitoring based on crop phenology. Therefore, time-series satellite images with a short period are required. However, there are limitations to acquiring time-series satellite data, so it is necessary to use fusion with other earth observation satellites. Before fusion of various satellite image data, it is necessary to overcome the inherent difference in radiometric characteristics of satellites. This study performed Korea Multi-Purpose Satellite-3 (KOMPSAT-3) cross calibration with Landsat-8 as the first step for fusion. Top of Atmosphere (TOA) Reflectance was compared by applying Spectral Band Adjustment Factor (SBAF) to each satellite using hyperspectral sensor band aggregation. As a result of cross calibration, KOMPSAT-3 and Landsat-8 satellites showed a difference in reflectance of less than 4% in Blue, Green, and Red bands, and 6% in NIR bands. KOMPSAT-3, without on-board calibrator, idicate lower radiometric stability compared to ladnsat-8. In the future, efforts are needed to produce normalized reflectance data through BRDF (Bidirectional reflectance distribution function) correction and SBAF application for spectral characteristics of agricultural land.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.351-358
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• 2008

KOMPSAT-5 will be launched in 2010 carrying a SAR (Synthetic Aperture Radar) system to obtain high resolution images of the earth surface regardless of weather or solar condition. In this paper, the orbits of KOMPSAT-5 and the imaging modes of SAR were analyzed for radargrammetry, and the best image pairs were suggested. We set the pass number from the nearest orbit to a given ground point and selected image pairs for radargrarnmetry, with height sensitivity of parallax higher than 0.5 to achieve enough height resolution and with the value lower than 0.8 to avoid errors from geometric distortion. On the equator, for example, where the distance between two adjacent passes is fixed to 95 km, we solved the orbit geometry and found that the image pairs with the pass numbers of 3-2 and 5-3 are suitable for radargrarnmetry. As the examples with arbitrary latitude, we selected Daejeon and Sejong Antarctic stations and calculated the orbital elements by using STK software. Three image pairs (5-4, 7-5 and 8-5) were found suitable for radargrammetry at Daejeon while 10 pairs (8-6, 9-7, 10-7, 11-8, 12-8, 13-9, 14-9, 15-9, 15-10 and 15-11) at Sejong Antarctic station.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.199-206
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• 2024

The GEO-KOMPSAT-2A (GK2A) satellite, which was launched in December 2018, carries weather observation payloads and uses the image navigation and registration system to calibrate the observation images. The calibration system requires accurate orbit prediction data and depends on the accuracy of the orbit determination accuracy. In order to find a possible way to improve the current orbit determination accuracy of the GK2A flight dynamic subsystem module, orbit determination software was developed to independently evaluate the orbit determination accuracy. A comprehensive satellite dynamic model is applied for a batch-type least squares filter. When determining the orbit, thrust firing during station-keeping maneuvers and wheel-off loading maneuvers is taken into account. One month of GK2A ranging data were processed to estimate the satellite position on a daily basis. The orbit determination error was evaluated by comparing estimates during overlapping estimation intervals.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1707-1720
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• 2023

With the increase in satellite time series data, the utility of remote sensing data is growing. In the analysis of time series data, the relative positional accuracy between images has a significant impact on the results, making image registration essential for correction. In recent years, research on image registration has been increasing by applying deep learning, which outperforms existing image registration algorithms. To train deep learning-based registration models, a large number of image pairs are required. Additionally, creating a correlation map between the data of existing deep learning models and applying additional computations to extract registration points is inefficient. To overcome these drawbacks, this study developed a data augmentation technique for training image registration models and applied it to OffsetNet, a registration model that predicts the offset amount itself, to perform image registration for KOMSAT-2, -3, and -3A. The results of the model training showed that OffsetNet accurately predicted the offset amount for the test data, enabling effective registration of the master and slave images.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.375-377
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• 2008

The KOMPSAT2 Terminal Polar Station was recently installed at near North Pole, Tromso, and Toulouse. The K2PS consists of one receiving station and two processing sites. The receiving station has been installed at SvalSat ($N78^{\circ}$, $E15^{\circ}$ ), and the two receiving sites have been installed at KSAT (Kongsberg Satellite Service AS), Tromso, Norway ($N69^{\circ}$ ,$E18^{\circ}$ ) and SISA, Toulouse, France ($N43^{\circ}$ ,$E1^{\circ}$ ). The products ofK2PS system can be classified to two categories: Level 1R product and Level 1G product. The Level 1R product is radiometric corrected product with RPC (Rational Polynomial Coefficients) and the Level 1G product is geometric corrected product with POD (Precise Orbit Data) and PAD (Precise Attitude Data) data based on Level 1R product. To meet a SISA (Spot Image SA)'s requirement, K2PS system has high performance product producing capability. This paper describes overall K2PS systems' production generation flow and the mass production test result of K2PS systems.

• Journal of Aerospace System Engineering
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• v.12 no.1
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• pp.10-16
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• 2018

In 2018 and 2019, GEO-KOMPSAT-2A and GEO-KOMPSAT-2B will be launched in order to succeed the COMS mission. The two satellites will be collocated in $128.25{\pm}0.05$ degrees East. For precise ranging and orbit determination, the GEO-KOMPSAT-2B will be equipped with LRA (Laser Retroreflector Assembly) and SLR (Satellite Laser Ranging) systems will be utilized. This systems are located in Geochang. In this case, the laser beam emitted from the SLR station can cause problems in terms of safety of optical payloads and image quality. As a solution of this possibility, the laser ranging will be done during the night time when the shutters of the optical payloads remain closed. Still, the optical payload of the GEO-KOMPSAT-2A is not safe from the laser beam because its optical payload shall continue its mission for 24 hours a day. In order to handle this problem, the laser ranging shall be limited to time slots when the angular distance between two satellites observed from the Geochang SLR station is large enough. In this paper, through orbit simulations, the characteristics of variation of the angular distance between the two satellites is analyzed to figure out the time slots when laser ranging is allowed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.4
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• pp.373-383
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• 2001

This study conducted pilot mapping project to know the possibility of mapping with medium resolution satellite imageries. For this purpose, mapping experiments were conducted with each stereo model imageries of SPOT, KOMPSAT, and IRS- lC. And positional accuracy, analysis of detectable and describable features, and comparison with existing digital map were checked, possible mapping scale and cost analysis were conducted with these results. Regarding SPOT imagery, digital photogrammetric workstation was used for stereoplotting. Regarding KOMPSAT and IRS-lC imageries, because there were data format support problems. head-up digitizing was performed with ortho imageries rectified with DEMs generated by image matching. The results of experiments show that such features as wide road, river, coast line, etc are possible to detect and depict but many other features are not for SPOT, KOMPSAT, and IRS-lC imageries. On the aspect of mapping, therefore, SPOT is available for 1/50,000 topographic map revision, KOMPSAT and IRS-lC for 1/25.000 topographic map revision.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1615-1627
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• 2020

The purpose of this study is to compare and analyze the performance of KOMPSAT-3 Digital Surface Model (DSM) made in overseas testbed area. To that end, we collected the KOMPSAT-3 in-track stereo image taken in San Francisco, the U.S. The stereo geometry elements (B/H, converse angle, etc.) of the stereo image taken were all found to be in the stable range. By applying precise sensor modeling using Ground Control Point (GCP) and DSM automatic generation technique, DSM with 1 m resolution was produced. Reference materials for evaluation and calibration are ground points with accuracy within 0.01 m from Compass Data Inc., 1 m resolution Elevation 1-DSM produced by Airbus. The precision sensor modeling accuracy of KOMPSAT-3 was within 0.5 m (RMSE) in horizontal and vertical directions. When the difference map was written between the generated DSM and the reference DSM, the mean and standard deviation were 0.61 m and 5.25 m respectively, but in some areas, they showed a large difference of more than 100 m. These areas appeared mainly in closed areas where high-rise buildings were concentrated. If KOMPSAT-3 tri-stereo images are used and various post-processing techniques are developed, it will be possible to produce DSM with more improved quality.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.66-80
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• 2012

It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.