• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.627-636
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• 2021

Although many studies on ship detection using synthetic aperture radar (SAR) satellite images are being conducted around the world, there are still very few employing SAR microsatellites, as most of the microsatellites are optical satellites. Recently, the ICEYE and Capella Space have embarked on the development of microsatellites with SAR sensor, and similar projects are being initiated globally in line with the flow of the new space era [e.g., for the ICEYE: 18 satellites (~2021); Capella Space: 36 satellites (~2023); and the Coast Guard SAR: 32 satellites in the early development stage]. In preparation for these new systems, it is important to review the SAR microsatellite system and the recent advances in this technology. Accordingly, in this paper, the current status and characteristics of optical and SAR microsatellite constellation operation are described, and studies using them are investigated. In addition, based on the status and characteristics of the representative SAR microsatellites, specifically the ICEYE and Capella systems, methods for using SAR microsatellite data for ship detection applications are described. Our results confirm that the SAR microsatellites operate as a constellation and have the advantages of short revisit cycles and quick provision of high-resolution images. With this technology, we expect SAR microsatellites to contribute greatly to the monitoring a wide-area target vessel, in which the spatiotemporal resolution of the imagery is especially important.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.3-16
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• 2011

천리안 위성은 4개 정부 부처 공동 사업으로, 통신 서비스, 해양 기상 관측 서비스 제공을 목적으로 개발된 복합 위성으로, 그중 통신 서비스를 담당하는 통신 탑재체는 방송통신위원회 출연으로 한국전자통신연구원(ETRI)가 주관, 개발하여 성공한 순수 국산 개발품으로, 위성 발사 성공 후 시험 검증을 거쳐 현재 정상 운용 중에 있다. 우주 인증 획득을 목적으로 개발한 통신 탑재체는 위성 스위칭 중계기와 다중 빔 안테나로 구성되었으며, 구성 부품들인 능동 부품과 수동 부품들은 대부분 국내 연구진에 의해 설계, 제작 시험 검증되어 중계기 및 안테나 시스템 종합화, 통신 탑재체 및 위성체 우주 환경 시험을 성공적으로 수행되었다. 위성 발사 성공 후에, 정지 궤도상에서의 통신 탑재체 궤도내 시험을 완료를 통해 순수국산 개발된 통신 탑재체의 설계 제작 기술에 대한 정지 궤도 우주환경에서도 정상 동작됨을 입증하였다. 통신 탑재체는 다양한 우주 조건에서의 다양한 기술 확보와 차세대 멀티미디어 위성 서비스 개발에 활용하고자 한다. 본 논문은 통해기 통신 탑재체 설계 제작 시험 기술을 소개하고, 활용 계획에 대해 언급하고자 한다.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.339-357
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• 2009

The Saemangeum Reclamation Project was launched as a national project in 1991 to reclaim a large coastal area of 401 km$^2$ by constructing a 33-km long dyke. The final dyke enclosure in April 2006 has transformed the tidal flat into lake and land. The dyke construction has abruptly changed not only the estuarine tidal system inside the dyke, but also the coastal marine environment outside the dyke. In this study, we investigated the spatial change of SST distribution using the Landsat-5/7 and NOAA data before and after the dyke completion in the Saemangeum area. Satellite-induced SST was verified by compared with the various in situ measurements such as tower, buoy, and water sample. The correlation coefficient resulted in above 0.96 and RMSE was about 1$^{\circ}C$ in all data. 38 Landsat satellite images from 1985 to 2007 were analyzed to estimate the temporal and spatial change of SST distribution from the beginning to the completion of the Samangeum dyke's construction. The seasonal change in detailed spatial distribution of SST was measured, however, the estimation of change during the Saemangeum dyke's construction was hard to figure out owing to the various environmental conditions. Monthly averaged SST induced from NOAA data from 1998 to 2007 has been analyzed for a complement of Landsat's temporal resolution. At the inside of the dyke, the change of SST from summer to winter was large due to the relatively high temperature in summer. In this study, multi-sensor thermal remote sensing is an efficient tool for monitoring the temporal and spatial distribution of SST in coastal area.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.1-10
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• 2009

We studied on the relationship between oceanic variation in the offshore and abnormal sea surface temperature rise in the coastal area of the Yellow Sea using a variety of satellite and in-situ data during winter 2004. In results of the satellite data, the average value of sea surface temperature in the Yellow Sea for 2003 was $10^{\circ}C$, and the average value of sea surface temperature for 2004 was $13^{\circ}C$. It was higher than those of the last year about $3^{\circ}C$. In results of the in-situ data, the average value of surface layer temperature in the Yellow Sea for 2003 was $9.85^{\circ}C$, and the average value of surface layer temperature for 2004 was $12.17^{\circ}C$. In the same satellite data, it was higher than those of the last year about $3^{\circ}C$. In results of the T-S diagram, we divided definitely into water mass of the Yellow Sea and the East China Sea in 2003. But we didn't divide definitely into water mass of the Yellow Sea and the East China Sea in 2004. The average values of air temperature and wind speed for 2003 were $5.23^{\circ}C$ and 4.81 m/s, respectively. And, the average values of air temperature and wind speed for 2004 were $5.61^{\circ}C$ and 4.52 m/s, respectively. So, These were similar. But the wind directions for 2003 were superior northwestern wind, and the wind directions for 2004 were various northern wind. The wind directions were different from each other. Therefore, the abnormal sea surface temperature rise in the coastal area of the Yellow Sea during winter 2004 were better related to oceanic variation in the offshore than influences of atmosphere. In the future, We will do in-depth study for these.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.435-444
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• 2009

In the case of oil spill accident at sea, information concerning the movement of spilled oil is important in making response strategies. Aircrafts and the satellites have been utilized for monitoring of spilled oil. In these days, numerical models are using to predict the movement of the spilled oil. In the future a coupling method of modeling and remote sensing data should be needed to predict more correctly the spilled oil. The purpose of this paper is to present an application of satellite image data to an oil spill prediction model as an initial condition. Environmental Fluid Dynamics Computer Code (EFDC) was used to predict the movement of the oil spilled from Hebei Spirit incident occurred in Taean coastal area on December 7,2007. In order to make the model initial condition and to compare the model results, two satellite images, KOMPSAT-2 MSC and ENVISAT ASAR obtained on December 8 and 11, were used during the period of the oil spill incident. The model results showed an improvement for the prediction of the spilled oil by using the initial condition deduced from satellite image data than the initial condition specified at the oil spill incident site in the respects of the distributed spilled area.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1207-1215
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• 2008

Satellite generates a complex electromagnetic noise by conducted and radiated coupling effect of the various electrical instruments. This noise may cause serious problems on the satellite system. To minimize the electromagnetic coupling effects and maintain the system safety margin, system noise reduction technique should be applied from the beginning of the system design. The COMS system is evaluated by measuring the conducted noise on system electrical power leads at PSR(Power Supply Regulator) and verifying a 6 dB system safety margin under the complex noise environment with current injection. The radiated noise due to the complex transmit antenna configuration is evaluated by integrating all unit-level RE measurement results, and the RF compatibility between spacecraft and launch vehicle is analyzed with the above estimations. This paper describes the COMS EMC compatibility analysis with respect to each unit level EMC test results, and RF compatibility analysis between spacecraft and launch vehicle. The analyzed results will be reflected on FM(Flight Model) EMC test.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.509-514
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• 2007

The importance of the GPS is becoming larger and larger since it is one of the Global Navigation Satellite Systems and is regarded as a national infrastructure in the field positioning and timing Nowadays many researches avoiding and/or minimizing economic loss caused by unexpected fault of the GPS are being carried out because GPS fault can give a large impact on social security system as well as economic system NDGPS network which has been authorized by the Ministry of Marine and Fisheries provides services for marine users and evolved into a national infrastructure for GNSS users. Many researchers and engineers are doing research work in order to apply the NDGPS network to other fields. From this trend, it can be expected that the integrity and related functions for the NDGPS users will become more important than before. This paper analyzes integrity informations about the real GNSS fault and proposes method on integrity monitoring improvement of the DGPS reference station.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1317-1328
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• 2021

This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (R_rc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' R_rc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.