• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.486-488
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• 2007

The Grid Reference System, which was firstly used in SPOT series, has been successfully adapted in KOMPSAT-1 and KOMPSAT-2 program, which identifies the geographical location to make image collection plans and manage the database of satellite images. Each Grid Reference System for KOMPSAT-1 and KOMPSAT-2 was designed based on system parameters related to each KOMPSAT-1 and KOMPSAT-2 and this fact leads to the need for the design of the Grid Reference System for KOMPSAT-3 (KGRS-3, hereafter), which reflects system parameters for KOMPSAT-3. The (K, J) coordinate system has been defined as the Grid Reference System for KOMPSAT-3 using heritages from KOMPSAT-1 and KOMPSAT-2 programs. The numbering of K begins with the prime meridian of K = 1 with running eastward on earth increasingly, and the numbering of J uses a value of J = 1000 at all points on the equator and begin with running northward increasingly. The Grid Reference System for KOMPSAT-3 is to be implemented in Ground Segment of KOMPSAT-3 system.

• 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.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.1-13
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• 2017

This study investigates the geometric and spatial image quality analysis of KOMPSAT-3A stereo pair. KOMPSAT-3A is, the latest satellite of KOMPSAT family, a Korean earth observation satellite operating in optical bands. A KOMPSAT-3A stereo pair was taken on 23 November, 2015 with 0.55 m ground sampling distance over Terrassa area of Spain. The convergence angle of KOMPSAT-3A stereo pair was estimated as $58.68^{\circ}$. The investigation was assessed through the evaluation of the geopositioning analysis, image quality estimation and the accuracy of automatic Digital Surface Model (DSM) generation and compared with those of KOMPSAT-3 stereo pair with the convergence angle of $44.80^{\circ}$ over the same area. First, geopositioning accuracy was tested with initial rational polynomial coefficients (RPCs) and after compensating the biases of the initial RPCs by manually collected ground control points. Then, regarding image quality, relative edge response was estimated for manually selected points visible from two stereo pairs. Both of the initial and bias-compensated positioning accuracy and the quality assessment result expressed that KOMPSAT-3A images showed higher performance than those of KOMPSAT-3 images. Finally, the accuracy of DSMs generated from KOMPSAT-3A and KOMPSAT-3 stereo pairs were examined with respect to the reference LiDAR-derived DSM. The various DSMs were generated over the whole coverage of individual stereo pairs with different grid spacing and over three types of terrain; flat, mountainous and urban area. Root mean square errors of DSM from KOMPSAT-3A pair were larger than those for KOMPSAT-3. This seems due to larger convergence angle of the KOMPSAT-3A stereo pair.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.327-343
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• 2020

This study proposes a method to improve the geometric quality of KOMPSAT (Korea Multi-Purpose Satellite)-3/3A Level 1R imagery, particularly for efficient disaster damage analysis. The proposed method applies a novel grid-based SIFT (Scale Invariant Feature Transform) method to the Planetscope ortho-imagery, which solves the inherent limitations in acquiring appropriate optical satellite imagery over disaster areas, and the KOMPSAT-3/3A imagery to extract GCPs (Ground Control Points) required for the RPC (Rational Polynomial Coefficient) bias compensation. In order to validate its effectiveness, the proposed method was applied to the KOMPSAT-3 multispectral image of Gangnueng which includes the April 2019 wildfire, and the KOMPSAT-3A image of Daejeon, which was additionally selected in consideration of the diverse land cover types. The proposed method improved the geometric quality of KOMPSAT-3/3A images by reducing the positioning errors(RMSE: Root Mean Square Error) of the two images from 6.62 pixels to 1.25 pixels for KOMPSAT-3, and from 7.03 pixels to 1.66 pixels for KOMPSAT-3A. Through a visual comparison of the post-disaster KOMPSAT-3 ortho-image of Gangneung and the pre-disaster Planetscope ortho-image, the result showed appropriate geometric quality for wildfire damage analysis. This paper demonstrated the possibility of using Planetscope ortho-images as an alternative to obtain the GCPs for geometric calibration. Furthermore, the proposed method can be applied to various KOMPSAT-3/3A research studies where Planetscope ortho-images can be provided.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1341-1350
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• 2019

This research deals with algorithm for forest fire severity classification using multi-temporal KOMPSAT-3A image to mapping forest fire areas. The recent satellite of the KOMPSAT series, KOMPSAT-3A, demonstrates high resolution and multi-spectral imagery with infrared and high resolution electro-optical bands. However, there is a lack of research to classify forest fire severity using KOMPSAT-3A. Therefore, the purpose of this study is to analyze forest fire severity using KOMPSAT-3A images. In addition, this research used pre-fire and post-fire Sentinel-2 with differenced Normalized Burn Ratio (dNBR) to taking for burn severity distribution map. To test the effectiveness of the proposed procedure on April 4, 2019, Gangneung wildfires were considered as a case study. This research used the probability density function for the classification of forest fire damage severity based on R software, a free software environment of statistical computing and graphics. The burn severities were estimated by changing NDVI before and after forest fire. Furthermore, standard deviation of probability density function was used to calculate the size of each class interval. A total of five distribution of forest fire severity were effectively classified.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• Atmosphere
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• v.16 no.4
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• pp.371-378
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• 2006

The surface observation probability system (SOPS) of the Korea Multi-Purpose Satellite (KOMPSAT) has been developed based on the climatological distribution of cloud coverage and the expected passage of satellite orbit. While the optical camera loaded on KOMPSAT series has been operated with the purpose of observing earth's surface, it cannot see the surface when an obstacle (i.e., cloud) exists between them. In the present study, cloud information of International Satellite Cloud Climatology Project incorporates into high resolution grid of the KOMPSAT-3 orbit. The characteristics of the KOMPSAT SOPS are discussed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.117-132
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• 2014

This paper had a purpose on analyzing result data from pan-sharpening, which have applied on the KOMPSAT-2 and -3 image. Particularly, the study focused on comparing each relative spectral response functions, which considers to cause color distortions of fused image. Two images from same time and location have been collected by KOMPSAT-2 and -3 to apply in the experiment. State-of-the-art algorithms of GIHS, GS1, GSA and GSA-CA were employed for analyzing the results in quantitatively and qualitatively. Following analysis of previous studies, GSA and GSA-CA methods resulted excellent quality in both of KOMPSAT-2/3 results, since they minimize spectral discordances between intensity and PAN image by the linear regression algorithm. It is notable that performances from KOMPSAT-2 and- 3 are not equal under same circumstances because of different spectral characteristics. In fact, KOMPSAT-2 is known as over-injection of low spatial resolution components of blue and green band, are greater than that of the PAN band. KOMPSAT-3, however, has been advanced in most of misperformances and weaknesses comparing from the KOMPSAT-2.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1179-1185
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• 2017

The KOMPSAT-3A satellite acquires high-resolution MWIR images twice a day compared to conventional Earth observing satellites. New radiometric information of Earth's surface can be provided due to different characteristics from existing SWIR images or TIR images. In this study, the difference image of multitemporal images was generated and compared with existing infrared images to find the characteristics of KOMPSAT-3A MWIR satellite images. A co-registration was performed and the difference between pixel values was minimized by using PIFs (Pseudo Invariant Features) pixel-based relative normalization. The experiment using Sentinel-2 SWIR image, Landsat 8 TIR image, and KOMPSAT-3A MWIR image showed that the distinction between artifacts in the difference image of KOMPSAT-3A is prominent. It is believed that the utilization of KOMPSAT-3A MWIR images can be improved by using the characteristics of IR image.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1935-1943
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• 2022

The development and application of a high-resolution soil moisture mapping method using satellite imagery has been considered one of the major research themes in remote sensing. In this study, soil moisture mapping in the test area of Jeju Island was performed. The soil moisture was calculated with optical images using linearly adjusted Synthetic Aperture Radar (SAR) polarization images and incident angle. SAR Backscatter data, Analysis Ready Data (ARD) provided by Google Earth Engine (GEE), was used. In the soil moisture processing process, the optical image was applied to normalized difference vegetation index (NDVI) by surface reflectance of KOMPSAT-3 satellite images and the land cover map of Environmental Systems Research Institute (ESRI). When the SAR image and the optical images are fused, the reliability of the soil moisture product can be improved. To validate the soil moisture mapping product, a comparative analysis was conducted with normalized difference water index (NDWI) products by the KOMPSAT-3 image and those of the Landsat-8 satellite. As a result, it was shown that the soil moisture map and NDWI of the study area were slightly negative correlated, whereas NDWI using the KOMPSAT-3 images and the Landsat-8 satellite showed a highly correlated trend. Finally, it will be possible to produce precise soil moisture using KOMPSAT optical images and KOMPSAT SAR images without other external remotely sensed images, if the soil moisture calculation algorithm used in this study is further developed for the KOMPSAT-5 image.