• Title/Summary/Keyword: KOMPSAT-2 영상

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Spaceborne High Resolution Imagery-Based Burn Severity Mapping (고해상도 위성화상(畵像)에 기초한 산불 피해 등급도 작성)

  • Kim, Choen;Hong, Sung-Hoo
    • Proceedings of the KSRS Conference
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    • 2008.03a
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    • pp.44-47
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    • 2008
  • 본 논문은 KOMPSAT-2호 및 3호의 화상활용 일환으로 고해상도 위성화상을 이용한 정량화 기반의 산불피해등급 분류도에 관한 시범연구이다. 무엇보다 중적외선 밴드가 없는 IKONOS화상에서 NBR산법개발과 NBR에 기초한 산불피해림의 등급분류도를 작성하였다. 본연구의 결과물인 삼척산불지역의 피해등급분류도는 -1과 1사이의 NBR 지수값을 갖는 8bit 회색조 영상을 심 중 경 구분의 산불피해등급별에 따라 각각 적 황 청색으로 나타낸 유색밀도편분 화상이다. 현지 실측의 CBI에 의한 검정에서 정밀 정확으로 평가될 경유, 고해상도 화상을 이용한 NBR기반의 산불피해등급 분류도는 산불 후 피해복구 선택, 즉 자연복원과 인공식재복원에 결정정보가 될 것이다.

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Optical Systems of the High-resolution Cameras for the KOMPSAT Payloads (다목적실용위성탑재 고해상도 카메라의 광학계 개발)

  • 이승훈;백홍열
    • Proceedings of the Optical Society of Korea Conference
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    • 2000.08a
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    • pp.36-37
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    • 2000
  • 정밀 지상관측 위성인 다목적실용위성 1호기에는 해상도 6.6 m인 전자광학카메라(EOC)가 탑재되어 현재 우수한 영상을 보내오고 있으며 2003년 발사예정인 2호기를 위하여 해상도 1 m의 Multispectral Camera(MSC)가 개발중이다. 미 TRW 사가 제작한 EOC 개발에 항우연의 연구진은 그 설계 및 시험의 각 단계별 검토와, 탑재, 위성전체 시험과 보정을 포함한 궤도운용 등의 수행과 함께, 개발기간 동안 현지에서 수행된 별도의 현장교육을 통하여 동급의 위성카메라를 실제 개발할 수 있는 설계기술을 이전받았다. 수차례 대구경 비구면 광학계 제작 경험을 더한 항우연은 MSC 공동개발선인 이스라엘 ELOP 사와 현재 그 설계를 진행하고 있다. (중략)

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Deep Learning-based Keypoint Filtering for Remote Sensing Image Registration (원격 탐사 영상 정합을 위한 딥러닝 기반 특징점 필터링)

  • Sung, Jun-Young;Lee, Woo-Ju;Oh, Seoung-Jun
    • Journal of Broadcast Engineering
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    • v.26 no.1
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    • pp.26-38
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    • 2021
  • In this paper, DLKF (Deep Learning Keypoint Filtering), the deep learning-based keypoint filtering method for the rapidization of the image registration method for remote sensing images is proposed. The complexity of the conventional feature-based image registration method arises during the feature matching step. To reduce this complexity, this paper proposes to filter only the keypoints detected in the artificial structure among the keypoints detected in the keypoint detector by ensuring that the feature matching is matched with the keypoints detected in the artificial structure of the image. For reducing the number of keypoints points as preserving essential keypoints, we preserve keypoints adjacent to the boundaries of the artificial structure, and use reduced images, and crop image patches overlapping to eliminate noise from the patch boundary as a result of the image segmentation method. the proposed method improves the speed and accuracy of registration. To verify the performance of DLKF, the speed and accuracy of the conventional keypoints extraction method were compared using the remote sensing image of KOMPSAT-3 satellite. Based on the SIFT-based registration method, which is commonly used in households, the SURF-based registration method, which improved the speed of the SIFT method, improved the speed by 2.6 times while reducing the number of keypoints by about 18%, but the accuracy decreased from 3.42 to 5.43. Became. However, when the proposed method, DLKF, was used, the number of keypoints was reduced by about 82%, improving the speed by about 20.5 times, while reducing the accuracy to 4.51.

A Study on Deep Learning Optimization by Land Cover Classification Item Using Satellite Imagery (위성영상을 활용한 토지피복 분류 항목별 딥러닝 최적화 연구)

  • Lee, Seong-Hyeok;Lee, Moung-jin
    • Korean Journal of Remote Sensing
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    • v.36 no.6_2
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    • pp.1591-1604
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    • 2020
  • This study is a study on classifying land cover by applying high-resolution satellite images to deep learning algorithms and verifying the performance of algorithms for each spatial object. For this, the Fully Convolutional Network-based algorithm was selected, and a dataset was constructed using Kompasat-3 satellite images, land cover maps, and forest maps. By applying the constructed data set to the algorithm, each optimal hyperparameter was calculated. Final classification was performed after hyperparameter optimization, and the overall accuracy of DeeplabV3+ was calculated the highest at 81.7%. However, when looking at the accuracy of each category, SegNet showed the best performance in roads and buildings, and U-Net showed the highest accuracy in hardwood trees and discussion items. In the case of Deeplab V3+, it performed better than the other two models in fields, facility cultivation, and grassland. Through the results, the limitations of applying one algorithm for land cover classification were confirmed, and if an appropriate algorithm for each spatial object is applied in the future, it is expected that high quality land cover classification results can be produced.

Relative RPCs Bias-compensation for Satellite Stereo Images Processing (고해상도 입체 위성영상 처리를 위한 무기준점 기반 상호표정)

  • Oh, Jae Hong;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.4
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    • pp.287-293
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    • 2018
  • It is prerequisite to generate epipolar resampled images by reducing the y-parallax for accurate and efficient processing of satellite stereo images. Minimizing y-parallax requires the accurate sensor modeling that is carried out with ground control points. However, the approach is not feasible over inaccessible areas where control points cannot be easily acquired. For the case, a relative orientation can be utilized only with conjugate points, but its accuracy for satellite sensor should be studied because the sensor has different geometry compared to well-known frame type cameras. Therefore, we carried out the bias-compensation of RPCs (Rational Polynomial Coefficients) without any ground control points to study its precision and effects on the y-parallax in epipolar resampled images. The conjugate points were generated with stereo image matching with outlier removals. RPCs compensation was performed based on the affine and polynomial models. We analyzed the reprojection error of the compensated RPCs and the y-parallax in the resampled images. Experimental result showed one-pixel level of y-parallax for Kompsat-3 stereo data.

The Application of Orbital Modeling and Rational Function Model for Ground Coordinate from High Resolution Satellite Data (고해상도 인공위성데이터로부터 지상좌표 결정을 위한 궤도모델링 및 RFM기법 적용)

  • Seo, Doo-Chun;Yang, Ji-Yeon;Lee, Dong-Han;Im, Hyo-Suk
    • Aerospace Engineering and Technology
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    • v.7 no.2
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    • pp.187-195
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    • 2008
  • Generation of accurate ground coordinates from high resolution satellite image are becoming increasingly of interest. The primary focus of this paper is to compute satellite direct sensor model (DSM) and rational function model (RFM) for accurate generation of ground coordinates from high resolution satellite images. Being based on this we presented an algorithm to be able to efficiently ground coordinates about large area with introducing RFM(rational function model) method applied to rigorous sensor modeling standing on basis of satellite orbit dynamics and collinearity equation, and sensor modeling of high-resolution satellite data like IKONOS, QuickBird, KOMPSAT-2 and others. The general high resolution satellite measures the position, velocity and attitude data of satellite using star, gyro, and GPS sensors.

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Analysis of NWP GRIB Data for LEO Satellite Mission Planning (저궤도 관측위성 임무계획(Mission Planning)을 위한 기상수치예보 GRIB Data 분석)

  • Seo Jeong-Soo;Seo Seok-Bae;Bae Hee-Jin;Kim Eun-Kyou
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.178-186
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    • 2006
  • 기상 수치예보는 (Numerical Weather Pridiction, NWP)는 바람, 기온, 등과 같은 기상요소의 시간 변화를 나타내는 물리방정식을 컴퓨터로 풀어 미래의 대기 상태를 예상하는 과학적인 방법으로 지구를 상세한 격자 2진부호(GRIdded Binary, 이하 GRIB)로 나누어 그 격자점에서의 값으로 대기 상태를 나타낸다. 지구 각지에서의 각종 관측자료를 기초로 격자점상의 현재값을 구한다. 대용량의 격자데이터는 이진형태이어서 컴퓨터, 서버 저장장치에서 동일형태 데이터로 존재한다. 우리나라 최초의 저궤도 관측 위성인 다목적 실용위성 KOMPSAT-1호(이하, 아리랑 위성1호)는 전자광학카메라(Electro Optical Camera, EOC)를 탑재하여 1999년 12월 21일에 발사된 이후 2006년 1월 현재까지 6여년간 성공적으로 임무를 수행, 7049여회의 영상을 획득하여 국가적으로 귀중한 자료로 활용하고 있다. 아리랑 위성1호는 일일 2-3회 EOC영상을 획득하고 있으며, 임무계획(Mission Planning)은 MP(Mission Planner)가 사용자로부터 자료를 수집하여 임무분석 및 계획 서브시스템(MAPS)에 의해 계산되어진 위성의 제도예측 데이터에 촬영하고자하는 목표지점 좌표를 입력하여 자동명령생성기(KSCG)에 의해 계산된 촬영 경사각도(Tilt)값을 위성에 전송하여 목표지역의 영상을 획득하게 된다. 위성영상 획득에 있어 고가의 위성을 운영하면서 기상의 상태를 정확히 예측하여 실패없이 유효한 영상을 획득하는 것이 무엇보다 중요하다. 본 논문에서는 효율적인 위성임무계획을 위한 기상수치예보 자료를 분석하여 앞으로 발사하게 될 고해상 카메라 탑제위성인 아리랑 위성2호와 3호에 적용하고자 한다. the sufficient excess reactivity to override this poisoning must be inserted, or its concentration is decreased sufficiently when its temporary shutdown is required. As ratter of fact, these have an important influence not only on reactor safety but also on economic aspect in operation. Considering these points in this study, the shutdown process was cptimized using the Pontryagin's maximum principle so that the shutdown mirth[d was improved as to restart the reactor to its fulpower at any time, but the xenon concentration did not excess the constrained allowable value during and after shutdown, at the same time all the control actions were completed within minimum time from beginning of the shutdown.및 12.36%, $101{\sim}200$일의 경우 12.78% 및 12.44%, 201일 이상의 경우 13.17% 및 11.30%로 201일 이상의 유기의 경우에만 대조구와 삭제 구간에 유의적인(p<0.05) 차이를 나타내었다.는 담수(淡水)에서 10%o의 해수(海水)

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Sensitivity Analysis for CAS500-4 Atmospheric Correction Using Simulated Images and Suggestion of the Use of Geostationary Satellite-based Atmospheric Parameters (모의영상을 이용한 농림위성 대기보정의 주요 파라미터 민감도 분석 및 타위성 산출물 활용 가능성 제시)

  • Kang, Yoojin;Cho, Dongjin;Han, Daehyeon;Im, Jungho;Lim, Joongbin;Oh, Kum-hui;Kwon, Eonhye
    • 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.

Calibration and Validation of Ocean Color Satellite Imagery (해양수색 위성자료의 검.보정)

  • ;B. G. Mitchell
    • Journal of Environmental Science International
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    • v.10 no.6
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    • pp.431-436
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    • 2001
  • Variations in phytoplankton concentrations result from changes of the ocean color caused by phytoplankton pigments. Thus, ocean spectral reflectance for low chlorophyll waters are blue and high chlorophyll waters tend to have green reflectance. In the Korea region, clear waters and the open sea in the Kuroshio regions of the East China Sea have low chlorophyll. As one moves even closer In the northwestern part of the East China Sea, the situation becomes much more optically complicated, with contributions not only from higher concentration of phytoplankton, but also from sediments and dissolved materials from terrestrial and sea bottom sources. The color often approaches yellow-brown in the turbidity waters (Case Ⅱ waters). To verify satellite ocean color retrievals, or to develop new algorithms for complex case Ⅱ regions requires ship-based studies. In this study, we compared the chlorophyll retrievals from NASA's SeaWiFS sensor with chlorophyll values determined with standard fluorometric methods during two cruises on Korean NFRDI ships. For the SeaWiFS data, we used the standard NASA SeaWiFS algorithm to estimate the chlorophyll_a distribution around the Korean waters using Orbview/ SeaWiFS satellite data acquired by our HPRT station at NFRDl. We studied In find out the relationship between the measured chlorophyll_a from the ship and the estimated chlorophyll_a from the SeaWiFs satellite data around the northern part of the East China Sea, in February, and May, 2000. The relationship between the measured chlorophyll_a and the SeaWiFS chlorophyll_a shows following the equations (1) In the northern part of the East China Sea. Chlorophyll_a =0.121Ln(X) + 0.504, R²= 0.73 (1) We also determined total suspended sediment mass (55) and compared it with SeaWiFS spectral band ratio. A suspended solid algorithm was composed of in-.situ data and the ratio (L/sub WN/(490 ㎚)L/sub WN/(555 ㎚) of the SeaWiFS wavelength bands. The relationship between the measured suspended solid and the SeaWiFS band ratio shows following the equation (2) in the northern part of the East China Sea. SS = -0.703 Ln(X) + 2.237, R²= 0.62 (2) In the near future, NFRDI will develop algorithms for quantifying the ocean color properties around the Korean waters, with the data from regular ocean observations using its own research vessels and from three satellites, KOMPSAT/OSMl, Terra/MODIS and Orbview/SeaWiFS.

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A Study of DEM Generation in the Ganghwado Southern Intertidal Flat Using Waterline Method and InSAR (수륙경계선 방법과 위상간섭기법을 이용한 강화도 남단 갯벌의 DEM 생성 연구)

  • Lee, Yoon-Kyung;Ryu, Joo-Hyung;Hong, Sang-Hoon;Won, Joong-Sun;Yoo, Hong-Rhyong
    • Journal of Wetlands Research
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    • v.8 no.3
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    • pp.29-38
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    • 2006
  • Digital Elevation Model (DEM) of intertidal flat can be widely used not only for scientific fields, coastal management, fisheries, ocean safety, military, but also for understanding natural and artificial topographic changes of the tidal flat. In this study, we generated DEM of the Ganghwado southern intertidal flat, the largest tidal flat in the west coast of the Korean Peninsula, using waterline method and interferometric synthetic aperture radar (InSAR). Constructed DEM which applied waterline method to the Landsat-5 TM and Landsat-7 ETM+ images closely expresses overall topographic relief of tidal flat. We found that the accuracy was determined by the number of waterlines which reflect various tidal conditions. The application of InSAR to the ERS-1/2 and ENVISAT images showed that only ERS-1/2 tandem pairs successfully generated DEM in the part of northern Yeongjongdo, but construction of DEM in the other areas was difficult due to the low coherence caused by a lot of surface remnant waters. In the near future, Kompsat-2 will provide satellite images having multi-spectral and high spatial resolution within a relatively short period at different sea levels. Application of waterline method to these images will help us construct a high precision tidal flat DEM. Also, we should develop DEM generation method using single-pass microwave satellite images.

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