• Title/Summary/Keyword: GOES-9

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GOES-9 위성 영상을 이용한 특정 궤도 지점에서의 지구 투영

  • Kang, Chi-Ho;Ahn, Sang-Il;Koo, In-Hoi
    • Aerospace Engineering and Technology
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    • v.3 no.1
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    • pp.267-271
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    • 2004
  • The satellite in the geostationary orbit rotates around Earth center with the same angular rate as the Earth. So, the Earth can be observed with sequential time series. GOES(Geostationary Operational Environmental Satellites)-9 is a meteorological satellite, which is now located at 155ㆁE geostationary orbit location in order to monitor East-Asia meteorological environment including Korean Peninsular. Every meteorological information is acquired from GOES-9 with the period of about 1 hour. COMS(Communication, Ocean and Meteorological Satellite) has been developed by KARI(Korea Aerospace Research Institute) since 2003 and will be launched at 2008. COMS will be located at different orbit location compared to GOES-9. In this study, a simulated COMS image which is the perspective from different geostationary orbit location is generated using an GOES-9 image.

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Investigation of Sensor Models for Precise Geolocation of GOES-9 Images (GOES-9 영상의 정밀기하보정을 위한 여러 센서모델 분석)

  • Hur, Dong-Seok;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • v.22 no.4
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    • pp.285-294
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    • 2006
  • A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigated three sensor models: collinearity model, direct linear transform (DLT) model and orbit-based model. We applied matching between GOES images and global coastline database and used successful results as control points. With control points we improved the initial image geolocation accuracy using the three models. We compared results from three sensor models. As a result, we showed that the orbit-based model is a suitable sensor model for precise geolocation of GOES-9 Images.

GOES-9 IMAGER DATA ANLYSIS FOR THE PREPRATION OF THE COMS MI OPERATION

  • LIM Hyun-Su;PARK Durk-Jong;KOO In-Hoi;KANG Chi-Ho
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.462-465
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    • 2005
  • The ITT Industry's Commercial Advanced Geo-Imager (CAGI) which is a recurrent version of imagers used in the GOES series was selected as the COMS Meteorological Imager (MI). The ITT Imager can conduct some special observation such as the space look, blackbody observation, and star sensing regularly or irregularly for its radiometric quality control. Because the GOES-9 which uses an ITT Imager has become operational over the Western Pacific and Eastern Asia positioned at 155 degrees East, the reception of the GOES-9 data is available in Korea. As a step of preparing the COMS MI operation, we conduct the analysis of the GOES-9 imager raw data and operation procedures and compare them with contents of the ITT Imager's manual.

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Investigation of Sensor Models for Precise Geolocation of GOES-9 Images

  • Hur Dongseok;Lee Tae-Yoon;Kim Taejung
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.91-94
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    • 2005
  • A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigate three sensor models: Collinearity model, Direct Linear Transform (DLT) model and Orbit-based model. We apply matching between GOES images and global coastline database and use successful results as control points. With control points we improve the initial image geolocation accuracy using the three models. We compare results from three sensor models that are applied to GOES-9 images. As a result, a suitable sensor model for precise geolocation of GOES-9 images is proposed.

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Utilizations of GOES-9 Data in METRI/KMA: Sea Surface Temperature, Atmospheric Motion Vector

  • Chung, Chu-Yong;Sohn, Eun-Ha;Ahn, Myoung-Hwan;Park, Hye-Sook
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.331-333
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    • 2003
  • KMA successfully began to receive and utilize the GOES-9 GVAR data since May 22nd 2003 when GOES-9 replaced the long-lived GMS-5 for Western Pacific and East Asian region until operation of MTSAT-1R in 2004. To take advantage of improvements of the GOES-9 data over the GMS-5 data, such as the increase of the temporal and spat ial resolution and addition of 3.9${\mu}$m channel, we have improved several algorithms to derive the meteorological products. Here we show two examples of algorithms, sea surface temperature and atmospheric motion vector, and preliminary results of validation of the improved algorithm.

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GOES-9 Raw Data Acquisition & Image Extraction

  • Kang C. H.;Park D. J.;Koo I. H.;Ahn S. I.;Kim E. K.
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.582-585
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    • 2005
  • The Geostationary Operational Environmental Satellite (GOES) 9, which is currently located at 155°E geostationary orbits, has transmitted earth observation data acquired by imager to CDA at NOAA. After the acquisition on ground, observation data are corrected on ground and re-transmitted to GOES-9 for the dissemination to users. In this paper, the procedure and result from raw data acquisition and pre-processing for earth observation imagery retrieval from GOES-9 Raw data acquired in Korea at May 2005 are introduced.

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The Study on The Consciousness of Housewives Eating Habit in Sang-Ju City according to ages (상주지역 주부의 식생활 의식 실태 조사(연령별))

  • Park, Eo-Jin;Park, Mo-Ra
    • Journal of the Korean Society of Food Culture
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    • v.16 no.3
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    • pp.225-234
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    • 2001
  • The purpose of this study was to know the conscious of eating habit of housewife. The data were collected from 250 housewives who were the age group of 20-60's in Sang-Ju. The survey was taken place from May to June in 2000. The result showed that there were significant differences in eating habit's consciousness according to housewife's age group: 1. As the age goes up, the housewife had less consideration herself when they purchased food and decided cooking method. 2. As the age goes down, the order in having meal was depended on conditions. But as the age goes up, they considered the order as important thing like followings; eating together, eating separately according to the sex, male first, senior first, housewives lastly. 3. The survey showed that there was distinction depending on sex in meal as age goes up. And The subject was conscious that the delicious and valuable meal served to male, senior and child before. 4. Regardless of senior, the consciousness for the skipping meal was high as the age goes down. 5. As the age goes up, female and seniors showed that leftover was not so good. 6. The consciousness that housewives were responsible for preparing the meal was high as the age goes up, but they had further difficulty in preparing meal as the age goes down. 7. In considering that male and senior should be participated in the kitchen work, they had high consciousness as the age goes down. 8. About role of cooking, the consciousness was hish in case of male as the age goes down, in case of female and housewife were high as the age goes up. 9. As the age goes up, The consciousness was high that Female must buy the food. 10. As the age goes up, they had high consciousness in considering that the meaning of meal was related to survival, that noodle and bread were not meal. And the consciousness about that eating out was not good for health was high as the age goes up.

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An Adjustment of Cloud Factors for Continuity and Consistency of Insolation Estimations between GOES-9 and MTSAT-1R (GOES-9과 MTSAT-1R 위성 간의 일사량 산출의 연속성과 일관성 확보를 위한 구름 감쇠 계수의 조정)

  • Kim, In-Hwan;Han, Kyung-Soo;Yeom, Jong-Min
    • Korean Journal of Remote Sensing
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    • v.28 no.1
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    • pp.69-77
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    • 2012
  • Surface insolation is one of the major indicators for climate research over the Earth system. For the climate research, long-term data and wide range of spatial coverage from the data observed by two or more of satellites of the same orbit are needed. It is important to improve the continuity and consistency of the derived products, such as surface insolation, from different satellites. In this study, surface insolations based on Geostationary Operational Environmental Satellite (GOES-9) and Multi-functional Transport Satellites (MTSAT-1R) were compared during overlap period using physical model of insolation to find ways to improve the consistency and continuity between two satellites through comparison of each channel data and ground observation data. The thermal infrared brightness temperature of two satellites show a relatively good agreement between two satellites : rootmean square error (RMSE)=5.595 Kelvin; Bias=2.065 Kelvin. Whereas, visible channels shown a quite different values, but it distributed similar tendency. And the surface insolations from two satellites are different from the ground observation data. To improve the quality of retrieved insolations, we have reproduced surface insolation of each satellite through adjustment of the Cloud Factor, and the Cloud Factor for GOES-9 satellite is modified based on the analysis result of difference channel data. As a result, the insolations estimated from GOES-9 for cloudy conditions show good agreement with MTSAT-1R and ground observation : RMSE=$83.439W\;m^{-2}$ Bias=$27.296W\;m^{-2}$. The result improved accuracy confirms that the modification of Cloud Factor for GOES-9 can improve the continuity and consistency of the insolations derived from two or more satellites.

A Study on the Algorithm for Estimating Rainfall According to the Rainfall Type Using Geostationary Meteorological Satellite Data (정지궤도 기상위성 자료를 활용한 강우유형별 강우량 추정연구)

  • Lee Eun-Joo;Suh Myoung-Seok
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.117-120
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    • 2006
  • Heavy rainfall events are occurred exceedingly various forms by a complex interaction between synoptic, dynamic and atmospheric stability. As the results, quantitative precipitation forecast is extraordinary difficult because it happens locally in a short time and has a strong spatial and temporal variations. GOES-9 imagery data provides continuous observations of the clouds in time and space at the right resolution. In this study, an power-law type algorithm(KAE: Korea auto estimator) for estimating rainfall based on the rainfall type was developed using geostationary meteorological satellite data. GOES-9 imagery and automatic weather station(AWS) measurements data were used for the classification of rainfall types and the development of estimation algorithm. Subjective and objective classification of rainfall types using GOES-9 imagery data and AWS measurements data showed that most of heavy rainfalls are occurred by the convective and mired type. Statistical analysis between AWS rainfall and GOES-IR data according to the rainfall types showed that estimation of rainfall amount using satellite data could be possible only for the convective and mixed type rainfall. The quality of KAE in estimating the rainfall amount and rainfall area is similar or slightly superior to the National Environmental Satellite Data and Information Service's auto-estimator(NESDIS AE), especially for the multi cell convective and mixed type heavy rainfalls. Also the high estimated level is denoted on the mature stage as well as decaying stages of rainfall system.

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Estimation of Rainfall Using GOES-9 Satellite Imagery Data (GOES-9호 위성 영상 자료를 이용한 강수량 산출)

  • 이정림;서명석;곽종흠;소선섭
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.209-214
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    • 2004
  • 국지적으로 단시간 내에 많은 양의 강한 비가 내리는 현상인 집중호우는 발생부터 성장, 쇠퇴까지의 과정이 단기간에 이루어지고, 그 변동성이 아주 크다. 그러므로 정확한 예보를 위해서는 단시간예보(nowcasting) 기법이 필요한데, 이를 위해서는 연속적이고, 정확한 관측이 필요하다. 집중호우의 관측에는 우량계, 레이다, 위성 관측 등이 사용되는데 이 연구에서는 GOES-9호 위성영상자료를 이용하였고, 2003년 여름의 8개 강수사례에 대해 분석하였다. 집중호우시의 강수량을 산출하기 위해 Power-law Curve를 사용하였고, NOAA/NESDIS에서 개발하여 현업에 사용 중인 Auto-Estimator의 무강수 픽셀 보정방법을 이용하여 산출된 강수량을 보정하였으며, 이를 기상청의 자동기상관측자료 (Automatic Weather Station: AWS)와 비교하였다. 위성영상자료의 시간 대표성을 분석하기 위해 위성의 관측 시간에 대해 전, 후, 중심을 기준으로 각각 15분, 30분, 60분 누적강수량과 비교하였고, AWS의 공간 대표성을 분석하기 위해 위성영상자료의 3×3, 5×5, 9×9 픽셀을 면적 평균하여 각각 비교하였다. 분석 결과 대부분의 사례에서 위성의 관측시간을 시작으로 60분 동안 누적한 강수량과 상관성이 가장 크게 나왔고, 면적에 대해서는 거의 차이가 없었다. 또한, 무강수 픽셀 보정방법의 하나로 구름의 성장률을 보정해 주었다. 그 결과 구름의 성장률을 보정해 주었을 때 상관계수가 0.05 이상 상승하였다.

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