• Title/Summary/Keyword: 해색위성

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Simulation and Evaluation of the KOMPSAT/OSMI Radiance Imagery (다목적 실용위성 해색센서 (OSMI)의 복사영상에 대한 모의 및 평가)

  • 반덕로;김용승
    • Korean Journal of Remote Sensing
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    • v.15 no.2
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    • pp.131-146
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    • 1999
  • The satellite visible data have been successfully applied to study the ocean color. Another ocean color sensor, the Ocean Scanning Multi-spectral Imager (OSMI) on the Korea Multi-Purpose Satellite (KOMPSAT) will be launched in 1999. In order to understand the characteristics of future OSMI images, we have first discussed the simulation models and procedures in detail, and produced typical patterns of radiances at visible bands by using radiative transfer models. The various simulated images of full satellite passes and Korean local areas for different seasons, water types, and the satellite crossing equator time (CET) are presented to illustrate the distribution of each component of radiance (i.e., aerosol scattering, Rayleigh scattering, sun glitter, water-leaving radiance, and total radiance). A method to evaluate the image quality and availability is then developed by using the characteristics of image defined as the Complex Signal Noise Ratio (CSNR). Meanwhile, a series of CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of OSMI images before the KOMPSAT will be placed in orbit. Finally, the quality and availability of OSMI images are quantitatively analyzed by the simulated CSNR image. It is hoped that the results would be useful to all scientists who are in charge of OSMI mission and to those who plan to use the data from OSMI.

Temporal and Spatial Distributions of Phytoplankton Pigment Concentration around the Korean Peninsula using Ocean Color Remote Sensing Imagery (해색위성영상을 활용한 한반도 주변 해역의 식물플랑크톤 색소농도의 시공간적 분포)

  • Kim Sang Woo;Cho Kyu Dae;Kim Young Seup;Kim Dong Sun;Choi Yoon Sun;Suh Young Sang
    • Proceedings of KOSOMES biannual meeting
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    • 2003.11a
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    • pp.191-193
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    • 2003
  • Temporal and spatial variability of phytoplankton pigment concentrations around the Korea Peninsula was described, using the monthly mean composite images of the SeaWiFS (Sea-Viewing Wide Field-of-View Sensor). The high pigment concentrations appear in the spring and fall in the East Sea The spring bloom in the southern regions (in April) occurs one month in advance in comparison with tint in the northern regions (in May). In summer season, the pigment concentrations are low all over the region in the East Sea And the high pigment concentrations exist yearly around warm stream along the coast of the East Sea, and in the coast of the West Sea and South Sea In particular, the high pigment concentrations linking near the mouth q the Yangze River to coast of South Sea in Korea appear during August to December.

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Development of the diffuse attenuation coefficient for down-welling irradiance ($K_d$) algorithm around the Korean Sea (우리나라 해역 특성에 맞는 수중에서의 하향 방향의 감쇠계수 알고리즘 ($K_d$ algorithm) 개발)

  • Min, Jee-Eun;Ryu, Joo-Hyung;Ahn, Yu-Hwan;Lee, Kyu-Sung
    • Proceedings of the KSRS Conference
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    • 2007.03a
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    • pp.204-209
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    • 2007
  • 수중에서의 하향 방향의 감쇠 계수 (Diffuse attenuation coefficient of down-welling irradiance, $K_d$)에 대한 연구는 상충 해양에 대한 열전달 수중에서의 광합성 및 다른 생물학적 과정에 대한 연구,해양 일차 생산력 추정, 대양 및 연안에서의 탁도 추정 등에 대한 연구의 보조 자료로서 해양원격탐사를 포함한 해양에 대한 연구에 매우 중요한 요소이다. 우리나라는 세계 최초의 정지궤도 해색 센서인 Geostationary Ocean Color Imager (GOCI)를 2008년 말에 통신해양기상위성 (COMS, Communication Ocean and Meteorological Satellite)에 탑재하여 쏘아 올릴 계획에 있다. 이 센서는 매일 한 시간 간격으로 한반도 주변 해역을 8회 이상 관측할 계획에 었다. 따라서 기존의 해색 센서들에 비해서 시간 해상도가 향상되기 때문에 해양 환경 모니터링에 있어서 많은 도움이 될 것으로 예상된다. 본 연구에서는 앞으로 운영될 GOCI 센서에 대한 수중에서의 하향 방향의 감쇠계수 (The diffuse attenuation coefficient of down-welling irradiance, $K_d$) 알고리즘을 현장 관측 값을 이용하여 미리 만들어 보고 이를 현재의 대표적인 해색 센서인 SeaWiFS 영상의$K_d$(490) product와 비교하여 보았다.

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Creating Atmospheric Scattering Corrected True Color Image from the COMS/GOCI Data (천리안위성 해양탑재체 자료를 이용한 대기산란 효과가 제거된 컬러합성 영상 제작)

  • Lee, Kwon-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.16 no.1
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    • pp.36-46
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    • 2013
  • The Geostationary Ocean Color Imager (GOCI), the first geostationary ocean color observation instrument launched in 2010 on board the Communication, Ocean, and Meteorological Satellite (COMS), has been generating the operational level 1 data. This study describes a methodology for creating the GOCI true color image and data processing software, namely the GOCI RGB maker. The algorithm uses a generic atmospheric correction and reprojection technique to produce the color composite image. Especially, the program is designed for educational purpose in a way that the region of interest and image size can be determined by the user. By distributing software to public, it would maximize the understanding and utilizing the GOCI data. Moreover, images produced from the geostationary observations are expected to be an excellent tool for monitoring environmental changes.

Monitoring of Floating Green Algae Using Ocean Color Satellite Remote Sensing (해색위성 원격탐사를 이용한 부유성 녹조 모니터링)

  • Lee, Kwon-Ho;Lee, So-Hyun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.3
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    • pp.137-147
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    • 2012
  • Recently, floating green algae (FGA) in open oceans and coastal waters have been reported over wide area, yet accurate detection of these using traditional ground based measurement and chemical analysis in the laboratory has been difficult or even impossible due to the lack of spatial resolution, coverage, and revisit frequency. In contrast, spectral reflectance measurement makes it possible to quickly assess the chlorophyll content in green algae. Our objectives are to investigate the spectral reflectance of the FGA observed in the Yellow Sea and to develop a new index to detect FGA from satellite imagery, namely floating green algae index (FGAI), which uses relatively simple reflectance ratio technique. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Geostationary Ocean Color Imager (GOCI) satellite images at 500m spatial resolution were utilized to produce FGAI which is defined as the ratio between reflectance at 860nm and 660nm bands. Both FGAI results yielded reasonable green algae detection at the regional scale distribution. Especially houly GOCI observations can present more detaield information of FGAI than low-orbit satellite.

Development of Korea Ocean Satellite Center (KOSC): System Design on Reception, Processing and Distribution of Geostationary Ocean Color Imager (GOCI) Data (해양위성센터 구축: 통신해양기상위성 해색센서(GOCI) 자료의 수신, 처리, 배포 시스템 설계)

  • Yang, Chan-Su;Cho, Seong-Ick;Han, Hee-Jeong;Yoon, Sok;Kwak, Ki-Yong;Yhn, Yu-Whan
    • Korean Journal of Remote Sensing
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    • v.23 no.2
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    • pp.137-144
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    • 2007
  • 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 2008. Ansan (the headquarter of KORDI) 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 into antenna and RF. Antenna is designed to be $\phi$ 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 arranged 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 offering received data to user less than an hour.

Introduction and Evaluation of the Production Method for Chlorophyll-a Using Merging of GOCI-II and Polar Orbit Satellite Data (GOCI-II 및 극궤도 위성 자료를 병합한 Chlorophyll-a 산출물 생산방법 소개 및 활용 가능성 평가)

  • Hye-Kyeong Shin;Jae Yeop Kwon;Pyeong Joong Kim;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1255-1272
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    • 2023
  • Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

A Study on the Detection and Statistical Feature Analysis of Red Tide Area in South Coast Using Remote Sensing (원격탐사를 이용한 남해안의 적조영역 검출과 통계적 특징 분석에 관한 연구)

  • Sur, Hyung-Soo;Lee, Chil-Woo
    • The KIPS Transactions:PartB
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    • v.14B no.2
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    • pp.65-70
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    • 2007
  • Red tide is becoming hot issue of environmental problem worldwide since the 1990. Advanced nations, are progressing study that detect red tide area on early time using satellite for sea. But, our country most seashores bends serious. Also because there are a lot of turbid method streams on coast, hard to detect small red tide area by satellite for sea that is low resolution. Also, method by sea color that use one feature of satellite image for sea of existent red tide area detection was most. In this way, have a few feature in image with sea color and it can cause false negative mistake that detect red tide area. Therefore, in this paper, acquired texture information to use GLCM(Gray Level Co occurrence Matrix)'s texture 6 information about high definition land satellite south Coast image. Removed needless component reducing dimension through principal component analysis from this information. And changed into 2 principal component accumulation images, Experiment result 2 principal component conversion accumulation image's eigenvalues were 94.6%. When component with red tide area that uses only sea color image and all principal component image. displayed more correct result. And divided as quantitative,, it compares with turbid stream and the sea that red tide does not exist using statistical feature analysis about texture.

Development $K_d({\lambda})$ and Visibility Algorithm for Ocean Color Sensor Around the Central Coasts of the Yellow Sea (황해 중부 연안 해역에서의 해색센서용 하향 확산 감쇠계수 및 수중시계 추정 알고리즘 개발)

  • Min, Jee-Eun;Ahn, Yu-Hwan;Lee, Kyu-Sung;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.23 no.4
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    • pp.311-321
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    • 2007
  • The diffuse attenuation coefficient for down-welling irradiance $K_d({\lambda})$, which is the propagation of down-welling irradiance at wavelength ${\lambda}$ from surface to a depth (z) in the ocean, and underwater visibility are important optical parameters for ocean studies. There have been several studies on $K_d({\lambda})$ and underwater visibility around the world, but only a few studies have focused on these properties in the Korean sea. Therefore, in the present study, we studied $K_d({\lambda})$ and underwater visibility around the coastal area of the Yellow Sea, and developed $K_d({\lambda})$ and underwater visibility algorithms for ocean color satellite sensor. For this research we conducted a field campaign around the Yellow Sea from $19{\sim}22$ September, 2006 and there we obtained a set of ocean optical and environmental data. From these datasets the $K_d({\lambda})$ and underwater visibility algorithms were empirically derived and compared with the existing NASA SeaWiFS $K_d({\lambda})$ algorithm and NRL (Naval Research Laboratory) underwater visibility algorithm. Such comparisons over a turbid area showed small difference in the $K_d({\lambda})$ algorithm and constants of our result for underwater visibility algorithm showed slightly higher values.

Introduction of Acquisition System, Processing System and Distributing Service for Geostationary Ocean Color Imager (GOCI) Data (정지궤도 해색탑재체(GOCI) 데이터의 수신.처리 시스템과 배포 서비스)

  • Yang, Chan-Su;Bae, Sang-Soo;Han, Hee-Jeong;Ahn, Yu-Hwan;Ryu, Joo-Hyung;Han, Tai-Hyun;Yoo, Hong-Rhyong
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.263-275
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    • 2010
  • KOSC(Korea Ocean Satellite Center), the primary operational organization for GOCI(Geostationary Ocean Color Imager), was established in KORDI(Korea Ocean Research & Development Institute). For a stable distribution service of GOCI data, various systems were installed at KOSC as follows: GOCI Data Acquisition System, Image Pre-processing System, GOCI Data Processing System, GOCI Data Distribution System, Data Management System, Total Management & Control System and External Data Exchange System. KOSC distributes the GOCI data 8 times to user at 1-hour intervals during the daytime in near-real time according to the distribution policy. Finally, we introduce the KOSC website for users to search, request and download GOCI data.