• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.939-948
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• 2020

CAS500-1 and CAS500-2 are high-resolution Earth-observing satellites being developed and scheduled to launch for land monitoring of Korea. The satellite information will be used for land usage analysis, change detection, 3D topological monitoring, and so on. Satellite image data of region of interests must be acquired in the stereo mode from different positions for 3D information generation. Accurate 3D processing and 3D display of stereo satellite data requires the epipolar image resampling process considering the pushbroom sensor and the satellite trajectory. This study developed an epipolar image resampling module for CAS-500 stereo data processing and verified its accuracy performance by testing along-track, across-track, and heterogeneous stereo data.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1029-1042
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• 2021

As part of the next-generation Compact Advanced Satellite 500 (CAS500) project, CAS500-4 is scheduled to be launched in 2025 focusing on the remote sensing of agriculture and forestry. To obtain quantitative information on vegetation from satellite images, it is necessary to acquire surface reflectance through atmospheric correction. Thus, it is essential to develop an atmospheric correction method suitable for CAS500-4. Since the absorption and scattering characteristics in the atmosphere vary depending on the wavelength, it is needed to analyze the sensitivity of atmospheric correction parameters such as aerosol optical depth (AOD) and water vapor (WV) considering the wavelengths of CAS500-4. In addition, as CAS500-4 has only five channels (blue, green, red, red edge, and near-infrared), making it difficult to directly calculate key parameters for atmospheric correction, external parameter data should be used. Therefore, thisstudy performed a sensitivity analysis of the key parameters (AOD, WV, and O₃) using the simulated images based on Sentinel-2 satellite data, which has similar wavelength specifications to CAS500-4, and examined the possibility of using the products of GEO-KOMPSAT-2A (GK2A) as atmospheric parameters. The sensitivity analysisshowed that AOD wasthe most important parameter with greater sensitivity in visible channels than in the near-infrared region. In particular, since AOD change of 20% causes about a 100% error rate in the blue channel surface reflectance in forests, a highly reliable AOD is needed to obtain accurate surface reflectance. The atmospherically corrected surface reflectance based on the GK2A AOD and WV was compared with the Sentinel-2 L2A reflectance data through the separability index of the known land cover pixels. The result showed that two corrected surface reflectance had similar Seperability index (SI) values, the atmospheric corrected surface reflectance based on the GK2A AOD showed higher SI than the Sentinel-2 L2A reflectance data in short-wavelength channels. Thus, it is judged that the parameters provided by GK2A can be fully utilized for atmospheric correction of the CAS500-4. The research findings will provide a basis for atmospheric correction of the CAS500-4 in the future.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.881-891
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• 2020

Recently, the Ministry of Land, Infrastructure and Transport and the Ministry of Science and ICT are developing the Land Observation Satellite (CAS-500) to meet increased demand for high-resolution satellite images. Expected image products of CAS-500 includes precision orthoimage, Digital Surface Model (DSM), change detection map, etc. The quality of these products is determined based on the geometric accuracy of satellite images. Therefore, it is important to make precision geometric corrections of CAS-500 images to produce high-quality products. Geometric correction requires the Ground Control Point (GCP), which is usually extracted manually using orthoimages and digital map. This requires a lot of time to acquire GCPs. Therefore, it is necessary to automatically extract GCPs and reduce the time required for GCP extraction and orthoimage generation. To this end, the Precision Image Processing (PIP) System was developed for CAS-500 images to minimize user intervention in GCP extraction. This paper explains the products, processing steps and the function modules and Database of the PIP System. The performance of the System in terms of processing speed, is also presented. It is expected that through the developed System, precise orthoimages can be generated from all CAS-500 images over the Korean peninsula promptly. As future studies, we need to extend the System to handle automated orthoimage generation for overseas regions.

• Smart Structures and Systems
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• v.24 no.6
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• pp.759-768
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• 2019

In nuclear fusion reactors, the key structural component (i.e., the plasma-facing component) undergoes high heat flux cyclic loading. To ensure the safety of fusion reactors, an experimental study on the temperature-induced creep of stainless steel under heat flux cyclic loading was performed in the present work. The strains were measured using a stereo digital image correlation technique (3D-DIC). The influence of the heat haze was eliminated, owing to the use of a vacuum environment. The specimen underwent heat flux cycles ($500^{\circ}C-1000^{\circ}C$) with different mechanical preloads (0 kN, 10 kN, 30 kN, and 50 kN). The results revealed that, for a relatively large preload (for example, 50 kN), a single temperature cycle can induce a residual strain of up to $15000{\mu}{\varepsilon}$.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.291-304
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• 2021

Updating a forest type map is essential for sustainable forest resource management and monitoring to cope with climate change and various environmental problems. According to the necessity of efficient and wide-area forestry remote sensing, CAS500-4 (Compact Advanced Satellite 500-4; The agriculture and forestry satellite) project has been confirmed and scheduled for launch in 2023. Before launching and utilizing CAS500-4, this study aimed to pre-evaluation the possibility of satellite-based tree species classification using RapidEye, which has similar specifications to the CAS500-4. In this study, the study area was the Chuncheon forest management complex, Gangwon-do. The spectral information was extracted from the growing season image. And the GLCM texture information was derived from the growing and non-growing seasons NIR bands. Both information were used to classification with random forest machine learning method. In this study, tree species were classified into nine classes to the coniferous tree (Korean red pine, Korean pine, Japanese larch), broad-leaved trees (Mongolian oak, Oriental cork oak, East Asian white birch, Korean Castanea, and other broad-leaved trees), and mixed forest. Finally, the classification accuracy was calculated by comparing the forest type map and classification results. As a result, the accuracy was 39.41% when only spectral information was used and 69.29% when both spectral information and texture information was used. For future study, the applicability of the CAS500-4 will be improved by substituting additional variables that more effectively reflect vegetation's ecological characteristics.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.917-927
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• 2020

The Ministry of Land, Infrastructure and Transport of Korea is developing a CAS 500-1/2 satellite capable of photographing a GSD 0.5 m level image, and is developing a technology to utilize this. Therefore, this study attempted to develop a geospatial feature extraction technique aimed at automation as a technique for utilizing CAS 500-1/2 satellite images. KOMPSAT-3A satellite images that are expected to be most similar to CAS 500-1/2 were used for research and the possibility of automation of geospatial feature extraction was analyzed through relative radiometric normalization. For this purpose, the parameters and thresholds were applied equally to the reference images and relative radiometric normalized images, and the geospatial feature were extracted. The qualitative analysis was conducted on whether the extracted geospatial feature is extracted in a similar form from the reference image and relative radiometric normalized image. It was also intended to analyze the possibility of automation of geospatial feature extraction by quantitative analysis of whether the classification accuracy satisfies the target accuracy of 90% or more set in this study. As a result, it was confirmed that shape of geospatial feature extracted from reference image and relative radiometric normalized image were similar, and the classification accuracy analysis results showed that both satisfies the target accuracy of 90% or more. Therefore, it is believed that automation will be possible when extracting spatial objects through relative radiometric normalization.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.891-907
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• 2023

Compact Advanced Satellite 500-4 (CAS500-4) is scheduled to be launched to collect high spatial resolution data focusing on vegetation applications. To achieve this goal, accurate surface reflectance retrieval through atmospheric correction is crucial. Therefore, a machine learning-based atmospheric correction algorithm was developed to simulate atmospheric correction from a radiative transfer model using Sentinel-2 data that have similarspectral characteristics as CAS500-4. The algorithm was then evaluated mainly for forest areas. Utilizing the atmospheric correction parameters extracted from Sentinel-2 and GEOKOMPSAT-2A (GK-2A), the atmospheric correction algorithm was developed based on Random Forest and Light Gradient Boosting Machine (LGBM). Between the two machine learning techniques, LGBM performed better when considering both accuracy and efficiency. Except for one station, the results had a correlation coefficient of more than 0.91 and well-reflected temporal variations of the Normalized Difference Vegetation Index (i.e., vegetation phenology). GK-2A provides Aerosol Optical Depth (AOD) and water vapor, which are essential parameters for atmospheric correction, but additional processing should be required in the future to mitigate the problem caused by their many missing values. This study provided the basis for the atmospheric correction of CAS500-4 by developing a machine learning-based atmospheric correction simulation algorithm.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.949-959
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• 2020

In this paper, as a prior study related to the generation of topographic information using the CAS500-1/2 satellite, we propose a method of extraction DSM for each 1:5000 scaled map in North Korea using KOMPSAT-3A strip images. This technique is designed to set the processing area by receiving shape file, only to generate output for every 1:5000 scaled map. In addition, dense point clouds and the DSM were extracted by applying MDR, a robust stereo image matching technique. Considering that the strip images are input in the units of scenes, we attempted to extract a DSM by processing and merging multiple image pairs in one 1:5000 map area. As a result, it was possible to confirm the generation of an integrated DSM with minimal separation at the junction, and as a result of the accuracy analysis, it was confirmed that the accuracy was within 5m compared to GCP.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.311-326
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• 2022

The Compact Advanced Satellite 500-4 (CAS500-4) is under development to efficiently manage and monitor forests in Korea and is scheduled to launch in 2025. The National Institute of Forest Science is developing 36 types of forestry applications to utilize the CAS500-4 efficiently. The products derived using the remote sensing method require validation with ground reference data, and the quality monitoring results for the products must be continuously reported. Due to it being the first time developing the national forestry satellite, there is no official calibration and validation site for forestry products in Korea. Accordingly, the author designed a calibration and validation site for the forestry products following international standards. In addition, to install calibration and validation sites nationwide, the authors selected appropriate sensors and evaluated the applicability of the sensors. As a result, the difference between the ground observation data and the Sentinel-2 image was observed to be within ±5%, confirming that the sensor could be used for nationwide expansion.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.40.2-40.2
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• 2020

500kg급 차세대중형위성은 공공분야 위성 수요에 효과적으로 대응하고, 국내 위성산업 저변 확대 및 산업체 육성을 위한 사업으로 개발되고 있다. 국내 산업체에서 개발되는 표준 위성 플랫폼이 적용될 예정인 차세대중형위성3호는 우주과학/기술검증용 위성으로, 특히 한국형발사체에 의해 2023년 발사된다는 점이 특별하다. 본 발표에서는 차세대 중형위성 3호에 제안한 우주망원경 UVOMPIS (UV-Optical Multiband Polarizing Imager System)에 대한 개념 설계 결과 및 과학 임무에 대한 소개를 통해 국내 학계와 산업계의 협력과 관심을 유도하고자 한다.