• Title/Summary/Keyword: KOMPSAT-3A

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Field Campaigns and test results for Absolute Radiometric Calibration (Absolute Radiometric Calibration을 위한 Field Campaign과 시험결과)

  • Lee, Seon-Gu;Kim, Yong-Seung
    • Aerospace Engineering and Technology
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    • v.5 no.2
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    • pp.213-219
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    • 2006
  • Korea Aerospace Research Institute(KARI) performed field campaigns for absolute radiometric calibration with overpassing of satellite Orbview-3 on Cal/ Val site in Goheung and Daejeon. The performed Cal/Val method is the reflectance-based of vicarious calibration methods. We collected ground-based and meteology data such as temperature, surface pressure and reflectance of targets, and radiosonde data only collected on Goheung. Data collected on each field served as input to radiative transfer codes to generate a top-of-atmosphere(TOA) radiance. Derived TOA is compared with DN of overpassing satellite Orbview-3 to calculate calibration coefficient of gain and offset. Also, This study proposed a proper method to prepare absolute radiometic calibration of KOMPSAT-2 by using experience of Field campaign.

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Change detection algorithm based on amplitude statistical distribution for high resolution SAR image (통계분포에 기반한 고해상도 SAR 영상의 변화탐지 알고리즘 구현 및 적용)

  • Lee, Kiwoong;Kang, Seoli;Kim, Ahleum;Song, Kyungmin;Lee, Wookyung
    • Korean Journal of Remote Sensing
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    • v.31 no.3
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    • pp.227-244
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    • 2015
  • Synthetic Aperture Radar is able to provide images of wide coverage in day, night, and all-weather conditions. Recently, as the SAR image resolution improves up to the sub-meter level, their applications are rapidly expanding accordingly. Especially there is a growing interest in the use of geographic information of high resolution SAR images and the change detection will be one of the most important technique for their applications. In this paper, an automatic threshold tracking and change detection algorithm is proposed applicable to high-resolution SAR images. To detect changes within SAR image, a reference image is generated using log-ratio operator and its amplitude distribution is estimated through K-S test. Assuming SAR image has a non-gaussian amplitude distribution, a generalized thresholding technique is applied using Kittler and Illingworth minimum-error estimation. Also, MoLC parametric estimation method is adopted to improve the algorithm performance on rough ground target. The implemented algorithm is tested and verified on the simulated SAR raw data. Then, it is applied to the spaceborne high-resolution SAR images taken by Cosmo-Skymed and KOMPSAT-5 and the performances are analyzed and compared.

Automated Image Matching for Satellite Images with Different GSDs through Improved Feature Matching and Robust Estimation (특징점 매칭 개선 및 강인추정을 통한 이종해상도 위성영상 자동영상정합)

  • Ban, Seunghwan;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1257-1271
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    • 2022
  • Recently, many Earth observation optical satellites have been developed, as their demands were increasing. Therefore, a rapid preprocessing of satellites became one of the most important problem for an active utilization of satellite images. Satellite image matching is a technique in which two images are transformed and represented in one specific coordinate system. This technique is used for aligning different bands or correcting of relative positions error between two satellite images. In this paper, we propose an automatic image matching method among satellite images with different ground sampling distances (GSDs). Our method is based on improved feature matching and robust estimation of transformation between satellite images. The proposed method consists of five processes: calculation of overlapping area, improved feature detection, feature matching, robust estimation of transformation, and image resampling. For feature detection, we extract overlapping areas and resample them to equalize their GSDs. For feature matching, we used Oriented FAST and rotated BRIEF (ORB) to improve matching performance. We performed image registration experiments with images KOMPSAT-3A and RapidEye. The performance verification of the proposed method was checked in qualitative and quantitative methods. The reprojection errors of image matching were in the range of 1.277 to 1.608 pixels accuracy with respect to the GSD of RapidEye images. Finally, we confirmed the possibility of satellite image matching with heterogeneous GSDs through the proposed method.

A Study on Method of Automatic Geospatial Feature Extraction through Relative Radiometric Normalization of High-resolution Satellite Images (고해상도 위성영상의 상대방사보정을 통한 자동화 지향 공간객체추출 방안 연구)

  • Lee, Dong-Gook;Lee, Hyun-Jik
    • 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.

A Suggestion for Surface Reflectance ARD Building of High-Resolution Satellite Images and Its Application (고해상도 위성 정보의 지표 반사도 Analysis-Ready Data (ARD) 구축과 응용을 위한 제언)

  • Lee, Kiwon;Kim, Kwangseob
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1215-1227
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    • 2021
  • Surface reflectance, as a product of the absolute atmospheric correction process of low-orbit satellite imagery, is the basic data required for accurate vegetation analysis. The Commission on Earth Observation Satellite (CEOS) has conducted research and guidance to produce analysis-ready data (ARD) on surface reflectance products for immediate use by users. However, this trend is still in the early stages of research dealing with ARD for high-resolution multispectral images such as KOMPSAT-3A and CAS-500, as it targets medium- to low-resolution satellite images. This study first summarizes the types of distribution of ARD data according to existing cases. The link between Open Data Cube (ODC), the cloud-based satellite image application platforms, and ARD data was also explained. As a result, we present practical ARD deployment steps for high-resolution satellite images and several types of application models in the conceptual level for high-resolution satellite images deployed in ODC and cloud environments. In addition, data pricing policies, accuracy quality issue, platform applicability, cloud environment issues, and international cooperation regarding the proposed implementation and application model were discussed. International organizations related to Earth observation satellites, such as Group on Earth Observations (GEO) and Committee on Earth Observation Satellites (CEOS), are continuing to develop system technologies and standards for the spread of ARD and ODC, and these achievements are expanding to the private sector. Therefore, a satellite-holder country looking for worldwide markets for satellite images must develop a strategy to respond to this international trend.

Satellite-based In-situ Monitoring of Space Weather: KSEM Mission and Data Application

  • Oh, Daehyeon;Kim, Jiyoung;Lee, Hyesook;Jang, Kun-Il
    • Journal of Astronomy and Space Sciences
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    • v.35 no.3
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    • pp.175-183
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    • 2018
  • Many recent satellites have mission periods longer than 10 years; thus, satellite-based local space weather monitoring is becoming more important than ever. This article describes the instruments and data applications of the Korea Space wEather Monitor (KSEM), which is a space weather payload of the GeoKompsat-2A (GK-2A) geostationary satellite. The KSEM payload consists of energetic particle detectors, magnetometers, and a satellite charging monitor. KSEM will provide accurate measurements of the energetic particle flux and three-axis magnetic field, which are the most essential elements of space weather events, and use sensors and external data such as GOES and DSCOVR to provide five essential space weather products. The longitude of GK-2A is $128.2^{\circ}E$, while those of the GOES satellite series are $75^{\circ}W$ and $135^{\circ}W$. Multi-satellite measurements of a wide distribution of geostationary equatorial orbits by KSEM/GK-2A and other satellites will enable the development, improvement, and verification of new space weather forecasting models. KSEM employs a service-oriented magnetometer designed by ESA to reduce magnetic noise from the satellite in real time with a very short boom (1 m), which demonstrates that a satellite-based magnetometer can be made simpler and more convenient without losing any performance.

CROP MANAGEMENT SYSTEM BASED ON HIGH SPATIAL RESOLUTION IMAGES

  • Kim Seong Joon;Kwon Hyung Joong;Park GeunAe;Lee Mi Seon
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.257-259
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    • 2005
  • A crop management system was developed using Visual Basic and ArcGIS VBA. The system is operated on ArcGlS 8.3 with Microsoft Access MOB. Landsat +ETM, KOMPSAT-l EOC, ASTER VNIR and IKONOS panchromatic (pan) and multi-spectral (MIS) images were included in the system to understand what kind of agriculture-related information can be extracted for each images. Agriculture related data inventories using crop cover information such as texture and average pixel value of the crop based on cultivation calendar were designed ,and implemented. Three IKONOS images (May 25,2001, December 25,2001, October 23,2003) were loaded in the system to show crop cover characteristics such as rice, pear, grape, red pepper, garlic, and surface water cover of reservoir with field surveys. GIS layers such as DEM (Digital Elevation Model), stream, road, soil, land use and administration boundary were also supplied and can be overlaid with images to enhance the understanding the general agricultural characteristics and identifying the location easily.

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Fuel Consumption Estimation for Atmospheric Drag Using LEO Perturbation Analysis (섭동해석을 이용한 저궤도 위성의 대기저항 보정용 연료 소모량 예측)

  • Jung, Do-Hee;Song, Yong-Kyu
    • Journal of Advanced Navigation Technology
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    • v.3 no.2
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    • pp.147-155
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    • 1999
  • In this work variations of orbital parameters are derived from the perturbation equations under Earth oblateness and atmospheric drag. A simple and effective scheme is proposed to compute the required delta v and fuel consumption to compensate for atmospheric drag. The scheme is applied to KOMPSAT example.

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위성탑재장비 장착패턴을 고려한 제작 오차 분석

  • Kim, Kyung-Won;Kim, Jin-Hee;Kim, Sung-Hoon;Lee, Ju-Hun;Hwang, Do-Soon
    • Aerospace Engineering and Technology
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    • v.3 no.2
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    • pp.20-24
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    • 2004
  • In this paper, a pattern/position tolerance analysis is visited on the insert to mount spacecraft electronic equipment. SQP(Sequential Quadratic Programming) is used to obtain the position tolerance. For examples, the cases of RDU(Remote Drive Unit) and OBC(On Board Computer) in the KOMPSAT-2 STM(Structure and Thermal Model) are analyzed.

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SEMI-AUTOMATIC EXTRACTION OF AGRICULTURAL LAND USE AND VEGETATION INFORMATION USING HIGH RESOLUTION SATELLITE IMAGES

  • Lee, Mi-Seon;Kim, Seong-Joon;Shin, Hyoung-Sub;Park, Jong-Hwa
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.147-150
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    • 2008
  • This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS satellite image (May 25 of 2001) and QuickBird satellite image (May 1 of 2006) which resembles with the spatial resolution and spectral characteristics of KOMPSAT3. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of vegetation information, three crops of paddy, com and red pepper were selected and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process is under development using the ERDAS IMAGINE Spatial Modeler Tool.

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