• 제목/요약/키워드: Ocean Color Imager

검색결과 161건 처리시간 0.023초

Spatial Gap-Filling of Hourly AOD Data from Himawari-8 Satellite Using DCT (Discrete Cosine Transform) and FMM (Fast Marching Method)

  • Youn, Youjeong;Kim, Seoyeon;Jeong, Yemin;Cho, Subin;Kang, Jonggu;Kim, Geunah;Lee, Yangwon
    • 대한원격탐사학회지
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    • 제37권4호
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    • pp.777-788
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    • 2021
  • Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

정지궤도 천리안위성 해양관측센서 GOCI의 Tasseled Cap 변환계수 산출연구 (A Study of Tasseled Cap Transformation Coefficient for the Geostationary Ocean Color Imager (GOCI))

  • 신지선;박욱;원중선
    • 대한원격탐사학회지
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    • 제30권2호
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    • pp.275-292
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    • 2014
  • 이 연구에서는 Geostationary Ocean Color Imager(GOCI) 센서에 적용할 수 있는 고유의 Tasseled Cap Transformation(TCT) 계수를 제시하고 있다. TCT는 다중밴드 센서 자료로부터 지표의 특성을 분석하는 전통적인 영상변환 방법 중 하나로 새로운 다중밴드 광학센서가 관측을 시작하는 경우 센서의 특성 차이로 인하여 각각의 육상관측 위성센서에 적합한 TCT 계수들이 장기 분석을 통하여 수립되어야 한다. GOCI 센서는 해양관측이 주 목적으로 개발되었으나 영상의 상당 부분은 육지를 관측하고 있으며 밴드 구성은 육지관측에도 일반적으로 이용되는 Visible-Near InfraRed(VNIR) 영역의 정보를 포함하고 있다. 또한 GOCI 센서의 높은 시간 해상도는 지표의 일별 변화의 관측에도 유용하게 사용될 수 있다. 이러한 장점을 이용하여 GOCI 센서에 대한 고유한 TCT가 제공된다면 GOCI 센서의 관측범위 내에서 준 실시간으로 지표변화에 대한 분석과 해석이 가능할 것이다. TCT는 일반적으로 "Brightness", "Greenness", "Wetness"의 세 가지 정보를 포함하지만, ShortWave InfraRed(SWIR) 파장대역이 없는 GOCI 센서의 경우에는 "Wetness"의 정보를 얻을 수 없다. GOCI 센서의 높은 시간 해상도의 활용을 극대화하기 위해서는 "Wetness"의 정보가 제공되어야 한다. "Wetness"의 정보를 얻기 위해 GOCI 주성분 분석(Principal Component Analysis: PCA) 공간을 MODIS TCT 공간에 선형 회귀하는 방법이 사용되었다. 이 연구에서 산출된 GOCI TCT 계수는 정지궤도의 특성에 의해 관측 시간대별로 다른 변환계수를 가질 수 있다. 이 차이를 알아보기 위하여 GOCI TCT 자료와 MODIS TCT 자료 사이의 상관관계가 비교되었다. 그 결과, "Brightness"와 "Greenness"는 4시 자료, "Wetness"는 2시 자료의 변환계수가 선택되었다. 최종적으로 산출된 변환계수의 적절성을 평가하기 위하여 GOCI TCT 자료는 MODIS TCT 영상 및 여러 육상 파라미터들과 비교되었다. GOCI TCT 영상은 MODIS TCT 영상보다 지표 피복의 분류가 더 세밀하게 표현되었으며, GOCI TCT 공간의 지표 피복 분포도 유의미한 결과를 보여줬다. 또한 GOCI TCT의 "Brightness", "Greenness", "Wetness" 자료는 Albedo($R^2$ = 0.75), Normalized Difference Vegetation Index(NDVI) ($R^2$ = 0.97), Normalized Difference Moisture Index(NDMI) ($R^2$ = 0.77)와 각각 비교적 높은 상관관계가 나타났다. 이러한 결과들은 적절한 TCT 계수의 산출이 이루어졌다는 것을 보여준다.

외삽법을 이용한 천리안위성 충격시험 분석 (COMS Shock Test Assessment by Using the Extrapolation Method)

  • 이호형
    • 한국항공우주학회지
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    • 제40권5호
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    • pp.439-445
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    • 2012
  • 천리안위성(COMS)은 발사체에 실려 비행하는 동안 발사체의 단이나 위성덮개가 분리될 때와 위성이 발사체로부터 분리될 때 충격 하중을 받는다. 그리고, 발사체에서 분리 후 태양전지판이 전개 전개될 때, 통신안테나가 전개될 때, 그리고 기상탑재체 라디에이터 덮개가 전개될 때 충격하중을 받게 된다. 이들 충격하중에 대한 위성의 안전 여부를 지상에서 검증하기 위하여 충격 시험이 수행되었다. 본 논문에서는 천리안위성 개발 과정 중에 수행된 충격시험과 시험분석 과정을 소개하고, 해양탑재체(해양관측카메라)의 예를 이용하여 시험 결과에 대한 분석 방법을 소개하였다. 아리안-5 발사체의 경우 위성분리를 위한 조임띠 해제 충격이 위성덮개나 단분리 충격보다 낮다. 본 논문에서는 위성분리 충격시험 결과를 이용하여 발사체로부터 위성이 받는 최대 충격을 고려하기 위한 외삽법 또한 소개되었다.

Delineation of Rice Productivity Projected via Integration of a Crop Model with Geostationary Satellite Imagery in North Korea

  • Ng, Chi Tim;Ko, Jonghan;Yeom, Jong-min;Jeong, Seungtaek;Jeong, Gwanyong;Choi, Myungin
    • 대한원격탐사학회지
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    • 제35권1호
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    • pp.57-81
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    • 2019
  • Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.

Tracing the trajectory of pelagic Sargassum using satellite monitoring and Lagrangian transport simulations in the East China Sea and Yellow Sea

  • Kwon, Kyungman;Choi, Byoung-Ju;Kim, Kwang Young;Kim, Keunyong
    • ALGAE
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    • 제34권4호
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    • pp.315-326
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    • 2019
  • Northeastward drifts of massive Sargassum patches were observed in the East China Sea (ECS) and Yellow Sea (YS) by the Geostationary Ocean Color Imager (GOCI) in May 2017. Coverage of the brown macroalgae patches was the largest ever recorded in the ECS and YS. Three-dimensional circulation modeling and Lagrangian particle tracking simulations were conducted to reproduce drifting trajectories of the macroalgae patches. The trajectories of the macroalgae patches were controlled by winds as well as surface currents. A windage (leeway) factor of 1% was chosen based on sensitivity simulations. Southerly winds in May 2017 contributed to farther northward intrusion of the brown macroalgae into the YS. Although satellite observation and numerical modeling have their own limitations and associated uncertainties, the two methods can be combined to find the best estimate of Sargassum patch trajectories. When satellites were unable to capture all patches because of clouds and sea fog in the ECS and YS, the Lagrangian particle tracking model helped to track and restore the missing patches in satellite images. This study suggests that satellite monitoring and numerical modeling are complementary to ensure accurate tracking of macroalgae patches in the ECS and YS.

Terra MODIS 위성영상과의 비교를 통한 COMS GOCI 위성영상의 식생지수 적용성 평가 (Applicability of Vegetation Indices from Terra MODIS and COMS GOCI Imageries)

  • 박진기;김봉섭;오시영;박종화
    • 한국농공학회논문집
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    • 제55권6호
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    • pp.47-55
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    • 2013
  • The objective of this study is to evaluate the applicability of Communication, Ocean, and Meteorological Satellite (COMS) Geostationary Ocean Color Imager (GOCI) vegetation indices on a quantitative analysis. For evaluation, the vegetation indices such as RVI, NDVI and SAVI were extracted by using COMS GOCI and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) imageries. The 4,000 points using simple random sampling (SRS) method were randomly extracted from land areas except ocean to compare the vegetation indices from two images. The results of linear regression showed that the regression coefficients of RVI, NDVI, and SAVI between COMS GOCI and Terra MODIS were 0.66~0.82, 0.71~0.83, and 0.71~0.83, respectively. Especially, the regression coefficients of RVI (r=0.85), NDVI (r=0.91) and SAVI (r=0.91) were strongly related from September 2011 to January 2012. Thus, COMS GOCI can be substituted for particular periods and it needs to verify additionally.

STATUS OF GOCI DATA PROCESSING SYSTEM(GDPS) DEVELOPMENT

  • Han, Hee-Jeong;Ahn, Yu-Hwan;Ryu, Joo-Hyung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.159-161
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    • 2007
  • Geostationary Ocean Color Imager (GOCI), the world-first ocean remote sensing instrument on geostationary Communication, Ocean, Meteorological Satellite (COMS), will be able to take a picture of a large region several times a day (almost with every one hour interval). We, KORDI, are in charge for developing the GOCI data processing system (GDPS) which is the basic software for processing the data from GOCI. The GDPS will be based on windows operating system to produce the GOCI level 2 data products (useful for oceanographic environmental analysis) automatically in real-time mode. Also, the GDPS will be a user-interactive program by well-organized graphical user interfaces for data processing and visualization. Its products will be the chlorophyll concentration, amount of total suspended sediments (TSS), colored dissolved organic matters (CDOM) and red tide from water leaving radiance or remote sensing reflectance. In addition, the GDPS will be able to produce daily products such as water current vector, primary productivity, water quality categorization, vegetation index, using individual observation data composed from several subscenes provided by GOCI for each slit within the target area. The resulting GOCI level 2 data will be disseminated through LRIT using satellite dissemination system and through online request and download systems. This software is carefully designed and implemented, and will be tested by sub-contractual company until the end of this year. It will need to be updated in effect with respect to new/improved algorithms and the calibration/validation activities.

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해양의 인공위성 자료 현황과 배포 소개 (Current Status of Ocean Satellite Remote Sensing Data and Its Distribution)

  • 양찬수
    • 해양환경안전학회:학술대회논문집
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    • 해양환경안전학회 2007년도 추계학술발표회
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    • pp.51-55
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    • 2007
  • As for satellite programs, the multipurpose satellite 1(KOMPSAT-1) was successfully launched on Dec. 21, 1999 and operated for three years. It is still properly operated even though its life cycle was ended. The development of KOMPSAT-2 (Korea Multipurpose Satellite-2) is near completion and the development of KOMPSAT-3, KOMPSAT-5 and COMS (Communication, Ocean, Meterological Satellite) are proceeding swiftly. In KORDI(Korea Ocean Research and Development Institute), the KOSC (Korea Ocean Satellite Center) construction project is being prepared for acquisition, processing and distribution of sensor data via L-band from GOCI(Geostationary Ocean Color Imager) instrument which is loaded on COMS(Communication, Ocean and Meteorological Satellite); it will be launched in 2000. Ansan(the headquarter of KORDD has been selected for the location of KOSC between 5 proposed sites, because it has the best condition to receive radio wave. The data acquisition system is classified antenna and RF. Antenna is designed to be ${\emptyset}$ 9m cassegrain antenna which has 19.35 $G/T(dB/^{\circ}K)$ at 1.67GHz, RF module, is divided into LNA(Low noise amplifier) and down converter, those are designed to send only horizontal polarization to modem The existing building is re-designed and classified for the KOSC operation concept; computing room, board of electricity, data processing room, operation room Hardware and network facilities have been designed to adapt for efficiency of each functions. The distribution system which is one of the most important systems will be constructed mainly on the internet, and it is also being considered constructing outer data distribution system as a web hosting service for to offering received data to user under an hour.

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THE KOMPSAT- I PAYLOADS OVERVIEW

  • Paik, Hong-Yul;Park, Gi-Hyuk;Youn, Hyeong-Sik;Lee, Seunghoon;Woo, Sun-Hee;Shim, Hyung-Sik;Oh, Kyoung-Hwan;Cho, Young-Min;Yong, Sang-Soon;Lee, Sang-Gyu;Heo, Haeng-Pal
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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    • pp.301-306
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    • 1998
  • Korea Aerospace Research Institute (KARI) is developing a Korea Multi-Purpose Satellite I (KOMPSAT-I) which accommodates Electro-Optical Camera (EOC), Ocean Scanning Multi-spectral Imager (OSMI), and Space Physics Sensor (SPS). The satellite has the weight of about 500kg and will be operated on the 10:50 AM sun-synchronized orbit with the altitude of 685 km. The satellite will be launched in 1999 and its lifetime is expected to be over 3 years. The main mission of EOC is the cartography to provide the images from a remote earth view for the production of 1/25000-scale maps of KOREA. EOC collects 510 ~ 730 nm panchromatic imagery with the ground sample distance(GSD) of 6.6 m and the swath width of 17 km by push broom scanning. EOC also can scan $\pm$45 degree across the ground track using body pointing method. The primary mission of OSMI is worldwide ocean color monitoring for the study of biological oceanography. It will generate 6 band ocean color images with 800 km swath width and 1km GSD by whiskbroom scanning. OSMI is designed to provide on-orbit spectral band selectability in the spectral range from 400 nm to 900 nm through ground command. This flexibility in band selection can be used for various applications and will provide research opportunities to support the next generation sensor design. SPS consists of High Energy Particle Detector (HEPD) and ionosphere Measurement Sensor (IMS). HEPD has missions 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 at the KOMPSAT orbit.

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MODIS Data를 이용한 GOCI의 적조 탐지 가능성에 대한 연구 (A Study on Possibility of Red Tide Detection Using MODIS Data)

  • 김용민;변영기;송우석;유기윤
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2007년도 춘계학술발표회 논문집
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    • pp.131-134
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    • 2007
  • In this paper, we evaluate a red tide detection possibility of GOCI(Geostationary Ocean Color Imager) which will be launched in 2008. To detect red tide, we use a similar wavelength range of MODIS normalized water-leaving radiance data instead of GOCI data. Supposed to GOCI, red tide detection algorithm is based on MRI(MODIS Red tide Index) and use 667nm band to filter turbid water. The algorithm's effectiveness is verified by detecting large Cochlodinium polykrikoides red tide event that was appeared in Korean coastal waters. The evaluation was done by comparing the result with the update data provided by the NFRDI.

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