• Title/Summary/Keyword: KOMPSAT-3A

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The Ground Checkout Test of OSMI on KOMPSAT-1

  • Yong, Sang-Soon;Shim, Hyung-Sik;Heo, Haeng-Pal;Cho, Young-Min;Oh, Kyoung-Hwan;Woo, Sun-Hee;Paik, Hong-Yul
    • Korean Journal of Remote Sensing
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    • v.15 no.4
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    • pp.297-305
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    • 1999
  • Ocean Scanning Multispectral Imager (OSMI) is a payload on the KOMPSAT satellite to perform global ocean color monitoring for the study of biological oceanography. The instrument images the ocean surface using a wisk-broom motion with a swath width of 800km and a ground sample distance (GSD) of < 1km over the entire field of view (FOV). The instrument is designed to have an on-orbit operation duty cycle of 20% over the mission lifetime of 3 years with the functions of programmable gain/offset and on-board image data compression/storage. The instrument also performs sun and dark calibration for on-board instrument calibration. The OSMI instrument is a multi-spectral imager covering the spectral range from 400nm to 900nm using CCD Focal Plane Array (FPA). The ocean colors are monitored using 6 spectral channels that can be selected via ground commands. KOMPSAT satellite with OSMI was integrated and the satellite level environment tests including instrument aliveness/functional test, such as launch environment, on-orbit environment (Thermal/Vacuum) and EMI/EMC test were performed at KARl. Test results met the requirements and the OSMI data were collected and analyzed during each test phase. The instrument is launched on the KOMPSAT satellite on December 21,1999 and is scheduled to start collecting ocean color data in the early 2000 upon completion of on-orbit instrument checkout.

The Trend of Satellite Mission Operations Team (위성 임무운영팀 동향)

  • Lee, Myeong-Shin;Jung, Ok-Chul;Chung, Dae-Won;Park, Sun-Ju;Shin, Jung-Hoon
    • Current Industrial and Technological Trends in Aerospace
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    • v.6 no.1
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    • pp.105-115
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    • 2008
  • The organization for satellite operation team is mainly based on the number of satellites to be controlled, operator's workload of payload operation support and the degree of automation of the operation system. Although the structure and its functionality of satellite operation organization are a little different according to the complexity of the operation, most satellite control centers have adapted the similar architecture for single or multiple satellite support. KARI Satellite Operation Center(KSOC) has started its simple mission operations since the launch of KOMPSAT-1(21st Dec. 1999) and has been evolving into multiple mission operations for various satellites such as KOMPSAT-2, KOMPSAT-3, KOMPSAT-5 and COMS(Communication Ocean Meteorological Satellite). This paper presents the appropriate direction of future deployment for KSOC by comparing the current status with the recommendation of the advanced satellite operation organization and analyzing their experiences in order to propose the better solution for efficient and safe satellite operations.

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Comparative Study of Deep Learning Model for Semantic Segmentation of Water System in SAR Images of KOMPSAT-5 (아리랑 5호 위성 영상에서 수계의 의미론적 분할을 위한 딥러닝 모델의 비교 연구)

  • Kim, Min-Ji;Kim, Seung Kyu;Lee, DoHoon;Gahm, Jin Kyu
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.206-214
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    • 2022
  • The way to measure the extent of damage from floods and droughts is to identify changes in the extent of water systems. In order to effectively grasp this at a glance, satellite images are used. KOMPSAT-5 uses Synthetic Aperture Radar (SAR) to capture images regardless of weather conditions such as clouds and rain. In this paper, various deep learning models are applied to perform semantic segmentation of the water system in this SAR image and the performance is compared. The models used are U-net, V-Net, U2-Net, UNet 3+, PSPNet, Deeplab-V3, Deeplab-V3+ and PAN. In addition, performance comparison was performed when the data was augmented by applying elastic deformation to the existing SAR image dataset. As a result, without data augmentation, U-Net was the best with IoU of 97.25% and pixel accuracy of 98.53%. In case of data augmentation, Deeplab-V3 showed IoU of 95.15% and V-Net showed the best pixel accuracy of 96.86%.

An Analysis of three-dimensional collision probability according to approaching objects to the KOMPSAT series (아리랑 위성들의 경향에 따른 및 3차원 충돌확률 분석)

  • Seong, Jae-Dong;Kim, Hae-Dong;Lim, Seong-Min
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.41 no.2
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    • pp.156-163
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    • 2013
  • Collision probability is the most common method to measure the risk of space debris, it is widely used that two dimensional linear collision probability using the closest approach distance. This paper represents the characteristics of object that approach KOMPSAT 2, 3, 5 that have operated or will be operated by Korea. And more precise method than two dimensional linear collision probability, we analyzed the properties of three dimensional nonlinear collision probability using STK/Nonlinear Collision Probability Tool. Through this, efficiency of three dimensional nonlinear collision probability for KOMPSAT series satellites was investigated. The result represents that three dimensional nonlinear collision probability showed the precise outcome at a relative velocity of less than 350m/s. Also, KOMPSAT series satellites appeared to few low relative velocity approaches and showed low efficiency for the three dimensional nonlinear collision probability.

Feasibility Assessment of Spectral Band Adjustment Factor of KOMPSAT-3 for Agriculture Remote Sensing (농업관측을 위한 KOMPSAT-3 위성의 Spectral Band Adjustment Factor 적용성 평가)

  • Ahn, Ho-yong;Kim, Kye-young;Lee, Kyung-do;Park, Chan-won;So, Kyu-ho;Na, Sang-il
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1369-1382
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    • 2018
  • As the number of multispectral satellites increases, it is expected that it will be possible to acquire and use images for periodically. However, there is a problem of data discrepancy due to different overpass time, period and spatial resolution. In particular, the difference in band bandwidths became different reflectance even for images taken at the same time and affect uncertainty in the analysis of vegetation activity such as vegetation index. The purpose of this study is to estimate the band adjustment factor according to the difference of bandwidth with other multispectral satellites for the application of KOMPSAT-3 satellite in agriculture field. The Spectral band adjustment factor (SBAF) were calculated using the hyperspectral satellite images acquired in the desert area. As a result of applying SBAF to the main crop area, the vegetation index showed a high agreement rate of relative percentage difference within 3% except for the Hapcheon area where the zenith angle was 25. For the estimation of SBAF, this study used only one set of images, which did not consider season and solar zenith angle of SBAF variation. Therefore, long-term analysis is necessary to solve SBAF uncertainty in the future.

Validation of Ship Detection by the RADARSAT Synthetic Aperture Radar and KOMPSAT EOC: Field Experiments (RADARSAT SAR와 KOMPSAT EOC에 의한 선박 탐지의 검증: 현장 실험)

  • Yang Chan-Su;Kim Sun-Young
    • Proceedings of KOSOMES biannual meeting
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    • 2004.11a
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    • pp.43-47
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    • 2004
  • Two different sensors (here, KOMPSAT and RADARSAT) are considered for ship detection, and are used to delineate the detection performance for their data The experiments are set for coastal regions of Mokpo Port and Ulsan Port and field experiments on board pilot boat are conducted to collect in situ ship validation information such as ship type and length This paper introduce mainly the experiment result of ship detection by both RADARSAT SAR imagery and land-based RADAR data, operated by the local Authority of South Korean, so called vessel traffic system (VTS) radar. Fine imagery of Ulsan Port was acquired on June 19, 2004 and in-situ data such as wind speed and direction, taking pictures of ships and natural features were obtained aboard a pilot ship. North winds, with a maximum speed of 3.1 m/s were recorded Ship's position, size and shape and natural features of breakwaters, oil pipeline and alongside ship were compared using SAR and VTS. It is shown that KOMPSAT/EOC has a good performance in the detection of a moving ship at a speed of kts or more an hour that ship and its wake can be imaged. The detection capability of RADARSAT doesn't matter how fast ship is running and depends on a ship itself, e.g. its material, length and type. Our results indicate that SAR can be applicable to automated ship detection for a VTS and SAR combination service.

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Analysis of Satellite Images to Estimate Forest Biomass (산림 바이오매스를 산정하기 위한 위성영상의 분석)

  • Lee, Hyun Jik;Ru, Ji Ho;Yu, Young Geol
    • 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.

Characteristics of Remote Sensors on KOMPSAT-I (다목적 실용위성 1호 탑재 센서의 특성)

  • 조영민;백홍렬
    • Korean Journal of Remote Sensing
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    • v.12 no.1
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    • pp.1-16
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    • 1996
  • Korea Aerospace Research Institute(KARI) is developing a Korea Multi-Purpose Satellite I(KOMPSAT-I) which accommodates Electro-Optical Camera(EOC), Ocean Color Imager(OCI), Space Physics Sensor(SPS) for cartography, ocean color monitoring, and space environment monitoring respectively. The satellite has the weight of about 500 kg and is operated on the sun synchronized orbit with the altitude of 685km, the orbit period of 98 minutes, and the orbit revisit time of 28days. The satellite will be launched in the third quarter of 1999 and its lifetime is more than 3 years. EOC has cartography mission to provide images for the production of scale maps, including digital elevation models, of Korea from a remote earth view in the KOMPSAT orbit. EOC collects panchromatic imagery with the ground sample distance(GSD) of 6.6m and the swath width of 15km at nadir through the visible spectral band of 510-730 nm. EOC scans the ground track of 800km per orbit by push-broom and body pointed method. OCI mission is worldwide ocean color monitoring for the study of biological oceanography. OCI is a multispectral imager generating 6 color ocean images with and <1km GSD by whisk-broom scanning method. OCI is designed to provide on-orbit spectral band selectability in the spectral range from 400nm to 900nm. The color images are collected through 6 primary spectral bands centered at 443, 490, 510, 555, 670, 865nm or 6 spectral bands selected in the spectral range via ground commands after launch. SPS consists of High Energy Particle Detector(HEPD) and Ionosphere Measurement Sensor(IMS). HEPD has mission to characterize the low altitude high energy particle environment and to study the effects of radiation environment on microelectronics. IMS measures densities and temperature of electrons in the ionosphere and monitors the ionospheric irregularities in KOMPSAT orbit.

Image Fusion Methods for Multispectral and Panchromatic Images of Pleiades and KOMPSAT 3 Satellites

  • Kim, Yeji;Choi, Jaewan;Kim, Yongil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.5
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    • pp.413-422
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    • 2018
  • Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

A Study on the Efficient Orthorectification of KOMPSAT Image (아리랑 영상의 효율적 정사보정처리 연구)

  • Oh, Kwan-Young;Lee, Kwang-Jae;Hwang, Jeong-In;Kim, Youn-Soo
    • Korean Journal of Remote Sensing
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    • v.37 no.6_3
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    • pp.2001-2010
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    • 2021
  • The purpose of this study is to efficiently improve orthorectification of KOMPSAT images. As the development of domestic and abroad earth observation satellites accelerates, the number and amounts of satellite images acquired are rapidly increasing. Accordingly, various studies are being conducted to improve orthorectification for the acquired image more quickly and efficiently. This study focused on enhancing processing efficiency through algorithm improvement, except for improving hardware computing capabilities such as GPU. Accordingly, the algorithm was improved with the LUT-based RFM method, and compared and analyzed in terms of accuracy and time-efficiency that vary depending on offset settings.