• 제목/요약/키워드: KOMPSAT-2 Satellite

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KOMPSAT-5 위성영상의 Coarse-to-fine SAR 오프셋트래킹 기법을 활용한 동남극 Campbell Glacier의 2차원 이동속도 관측 (Two-dimensional Velocity Measurements of Campbell Glacier in East Antarctica Using Coarse-to-fine SAR Offset Tracking Approach of KOMPSAT-5 Satellite Image)

  • 채성호;이광재;이선구
    • 대한원격탐사학회지
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    • 제37권6_3호
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    • pp.2035-2046
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    • 2021
  • 빙하 이동속도는 빙하역학 연구에 가장 기초가 되는 관측치로 기후 변화에 따른 해수면 상승 등을 예측하는데 매우 중요한 지시자이다. 본 연구에서는 SAR 오프셋트래킹 기법을 통해 동남극 테라노바 만에 위치한 Campbell Glacier에 대한 2차원 이동속도를 관측하였다. 이를 위하여 연구지역에 대하여 2021년 7월 9일과 2021년 8월 6일에 촬영한 국내 KOMPSAT-5 SAR 위성영상을 획득하였다. 선행 연구를 통하여 제안한 다중변위커널을 활용한 오프셋트래킹 기법은 해상도와 정밀도를 모두 만족하는 최적의 결과를 얻는 기법이다. 하지만 커널 크기에 따라 오프셋트래킹을 반복하여 수행하기 때문에 매우 집약적인 연산 능력과 시간이 필요하게 된다. 따라서 본 연구에서는 전략적으로 coarse-to-fine SAR 오프셋트래킹 방법을 고안하였다. coarse-to-fine 오프셋트래킹을 통하여 일반적인 오프셋트래킹 결과보다 해상도는 유지되고 정밀도는 향상(특히, 비행방향으로 약 4배)된 결과를 획득할 수 있다. 이 기법을 활용하여 Campbell Glacier에 대한 2차원 이동속도 영상을 생성하였다. 2차원 이동속도 영상을 분석한 결과 Campbell Glacier의 지반선(grounding line)은 대략 위도 -74.56N 부근에 존재하는 것으로 관측할 수 있었다. 이 연구에서 분석된 Campbell Glacier Tongue의 흐름속도(185-237 m/yr)는 1988-1989년의 흐름속도(140-240 m/yr)에 비하여 증가하였다. 그리고 2010-2012년의 흐름속도(181-268 m/yr)에 비하여 지반선 부근에서 이동속도는 유사하였지만 Campbell Glacier Tongue의 끝부분에서의 이동속도는 감소한 것을 확인할 수 있었다. 하지만 이는 본 연구의 연구 결과는 28일 동안 발생한 빙하의 이동속도를 연간 속도로 환산한 것이기 때문에 발생하는 오차일 가능성이 있다. 향후 정확한 비교를 위해서는 시계열적으로 자료를 확장하여 연간 속도를 정확하게 계산하는 과정이 필요할 것이다. 이 연구를 통해 최초로 국내 X-밴드 SAR 위성인 KOMPSAT-5 위성 영상을 활용하여 빙하의 2차원 이동속도를 관측하였으며, KOMPSAT-5 영상의 coarse-to-fine SAR 오프셋트래킹 기법이 빙하의 2차원 이동속도 관측에 매우 유용함을 확인할 수 있었다.

KOMPSAT-2 위성영상을 이용한 불투수지도작성 방법에 관한 실증연구 (A Study on Empirical Method Analysis of Impervious Surface Using KOMPSAT-2 Image)

  • 배다혜;이재일;고창환;하성룡
    • 환경영향평가
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    • 제20권5호
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    • pp.717-727
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    • 2011
  • Impervious surface affects urban climate, flood, and water pollution and has important role as basic data for urban planning and environmental and resources management uses. With a high paved rate, increased quantity of the outflown water and brings urban flooding during a heavy rain. Moreover, these non-point source pollution is getting increased the water pollution. In this regard, it is definitely important to research and keep monitoring the current situation of paved surface, which influences urban ecosystem, disaster and pollution. In this study, we suggest a method to utilize high resolution satellite image data for efficient survey on the current condition of paved surface. We analysed the paved surface condition of Dae-jeon metropolitan city area using KOMPSAT-2 image and validate its practicalness and limitation of this method.

KOMPSAT-2 영상을 이용한 토지피복정보 자동 추출 (Automatic Extraction of Land Cover information By Using KOMPSAT-2 Imagery)

  • 이현직;유지호;유영걸
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2010년 춘계학술발표회 논문집
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    • pp.277-280
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    • 2010
  • There is a need to convert the old low- or medium-resolution satellite image-based thematic mapping to the high-resolution satellite image-based mapping of GSD 1m grade or lower. There is also a need to generate middle- or large-scale thematic maps of 1:5,000 or lower. In this study, the DEM and orthoimage is generated with the KOMPSAT-2 stereo image of Yuseong-gu, Daejeon Metropolitan City. By utilizing the orthoimage, automatic extraction experiments of land cover information are generated for buildings, roads and urban areas, raw land(agricultural land), mountains and forests, hydrosphere, grassland, and shadow. The experiment results show that it is possible to classify, in detail, for natural features such as the hydrosphere, mountains and forests, grassland, shadow, and raw land. While artificial features such as roads, buildings, and urban areas can be easily classified with automatic extraction, there are difficulties on detailed classifications along the boundaries. Further research should be performed on the automation methods using the conventional thematic maps and all sorts of geo-spatial information and mapping techniques in order to classify thematic information in detail.

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기계학습 기법에 따른 KOMPSAT-3A 시가화 영상 분류 - 서울시 양재 지역을 중심으로 - (KOMPSAT-3A Urban Classification Using Machine Learning Algorithm - Focusing on Yang-jae in Seoul -)

  • 윤형진;정종철
    • 대한원격탐사학회지
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    • 제36권6_2호
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    • pp.1567-1577
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    • 2020
  • 시가화 지역 토지피복분류는 도시계획 및 관리에 활용된다. 따라서, 시가화 지역에 대한 분류 정확도 향상 연구는 중요하다고 할 수 있다. 본 연구에서는 고해상도 위성영상인 KOMPSAT-3A을 기계학습 중 Support Vector Machine(SVM)과 Artificial Neural Network(ANN)을 기반으로 시가화지역 분류를 진행하였다. 훈련 데이터 구축과정에서 25 m 격자를 기반으로 훈련 지역을 구분하여 영상을 학습하였으며, 학습된 모델을 활용하여 테스트 지역을 분류하였다. 검증과정에서 250개의 GTP를 활용하여 오차 행렬을 통한 결과를 제시하였다. SVM 4가지 기법과 ANN 2가지 기법 중 SVM Polynomial Model이 가장 높은 정확도인 86%를 나타냈다. Ground Truth Points(GTP)를 활용하여 두 개의 모델을 비교하는 과정에서, SVM 모델은 전체적으로 ANN 모델보다 효과적으로 KOMPSAT-3A 영상을 분류하였다. 건물, 도로, 식생, 나대지 4가지 클래스 분류 중 건물이 가장 낮은 분류정확도를 보여주었으며, 이는 고층건물에 따른 건물 그림자에 의한 오분류가 주요 원인으로 나타났다.

SATELLITE MONITORING OF OIL SPILLS CAUSED BY THE HEBEI SPIRIT ACCIDENT

  • Yang, Chan-Su;Yeom, Gi-Ho;Chang, Ji-Seong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.368-368
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    • 2008
  • Oil spills are a principal factor of the ocean pollution. The complicated problems involved in detecting oil spills are usually due to varying wind and sea surface condition such as ocean wave and current. The Hebei Spirit accident was happened in the west sea ($36^{\circ}$41'04" N, $126^{\circ}$03'12" E) near about 8 km distant from Tae-An, Korea on December 7, 2007. The aim of this work is to improve the detection and classification performance in order to define a more accurate training set and identifying the feature of oil spill region. This paper deals with an optimization technique for the detection and classification scheme using multi-frequency and multi-polarization SAR and optical image data sets of the oil spilled sea. The used image data are the ENVISAT ASAR WS and Radarsat-1 of C-band and ALOS PALSAR of L-band SAR data and KOMPSAT-2 optical images together with meteorological or oceanographic data. Both the theory and the experimental results obtained are discussed.

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Derivation of Surface Temperature from KOMPSAT-3A Mid-wave Infrared Data Using a Radiative Transfer Model

  • Kim, Yongseung
    • 대한원격탐사학회지
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    • 제38권4호
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    • pp.343-353
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    • 2022
  • An attempt to derive the surface temperature from the Korea Multi-purpose Satellite (KOMPSAT)-3A mid-wave infrared (MWIR) data acquired over the southern California on Nov. 14, 2015 has been made using the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer model. Since after the successful launch on March 25, 2015, the KOMPSAT-3A spacecraft and its two payload instruments - the high-resolution multispectral optical sensor and the scanner infrared imaging system (SIIS) - continue to operate properly. SIIS uses the MWIR spectral band of 3.3-5.2 ㎛ for data acquisition. As input data for the realistic simulation of the KOMPSAT-3A SIIS imaging conditions in the MODTRAN model, we used the National Centers for Environmental Prediction (NCEP) atmospheric profiles, the KOMPSAT-3Asensor response function, the solar and line-of-sight geometry, and the University of Wisconsin emissivity database. The land cover type of the study area includes water,sand, and agricultural (vegetated) land located in the southern California. Results of surface temperature showed the reasonable geographical pattern over water, sand, and agricultural land. It is however worthwhile to note that the surface temperature pattern does not resemble the top-of-atmosphere (TOA) radiance counterpart. This is because MWIR TOA radiances consist of both shortwave (0.2-5 ㎛) and longwave (5-50 ㎛) components and the surface temperature depends solely upon the surface emitted radiance of longwave components. We found in our case that the shortwave surface reflection primarily causes the difference of geographical pattern between surface temperature and TOA radiance. Validation of the surface temperature for this study is practically difficult to perform due to the lack of ground truth data. We therefore made simple comparisons with two datasets over Salton Sea: National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) field data and Salton Sea data. The current estimate differs with these datasets by 2.2 K and 1.4 K, respectively, though it seems not possible to quantify factors causing such differences.

IKONOS 영상자료를 이용한 농업관련 토지피복 분류기준 설정 연구 (Standardizing Agriculture-related Land Cover Classification Scheme Using IKONOS Satellite Imagery)

  • 홍성민;정인균;김성준
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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    • pp.261-265
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    • 2004
  • The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat+ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

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Geolocation Error Analysis of KOMPSAT-5 SAR Imagery Using Monte-Carlo Simulation Method

  • Choi, Yoon Jo;Hong, Seung Hwan;Sohn, Hong Gyoo
    • 한국측량학회지
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    • 제37권2호
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    • pp.71-79
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    • 2019
  • Geolocation accuracy is one of the important factors in utilizing all weather available SAR satellite imagery. In this study, an error budget analysis was performed on key variables affecting on geolocation accuracy by generating KOMPSAT-5 simulation data. To perform the analysis, a Range-Doppler model was applied as a geometric model of the SAR imagery. The results show that the geolocation errors in satellite position and velocity are linearly related to the biases in the azimuth and range direction. With 0.03cm/s satellite velocity biases, the simulated errors were up to 0.054 pixels and 0.0047 pixels in the azimuth and range direction, and it implies that the geolocation accuracy is sensitive in the azimuth direction. Moreover, while the clock drift causes a geolocation error in the azimuth direction, a signal delay causes in the range direction. Monte-Carlo simulation analysis was performed to analyze the influence of multiple geometric error sources, and the simulated error was up to 3.02 pixels in the azimuth direction.