• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2936-2951
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• 2016

An emerging satellite technology, Operationally Responsive Space (ORS) is expected to provide a fast and flexible solution for emergency response, such as target tracking, dense earth observation, communicate relaying and so on. To realize large distance transmission, we propose the use of available relay satellites as relay nodes. Accordingly, we apply software defined network (SDN) technology to ORS networks. We additionally propose a satellite network architecture refered to as the SDN-based ORS-Satellite (Sat) networking scheme (SDOS). To overcome the issures of node failures and dynamic topology changes of satellite networks, we combine centralized and distributed routing mechanisms and propose a fast recovery routing algorithm (FRA) for SDOS. In this routing method, we use centralized routing as the base mode.The distributed opportunistic routing starts when node failures or congestion occur. The performance of the proposed routing method was validated through extensive computer simulations.The results demonstrate that the method is effective in terms of resoving low end-to-end delay, jitter and packet drops.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.10a
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• pp.139-143
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• 2009

• Journal of the Korean Society for Precision Engineering
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• v.27 no.12
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• pp.9-14
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• 2010

Using an IR (infrared) optical system of observation and research were performed long before. Nowadays satellites equipped with IR optical system observe the earth and universe. In this paper, we developed the IR optical system for main payload of the STSAT-3 (Science and Technology Satellite -3). We studied the ultra precision machining technique to fabricate FPL-53 lenses which is the IR optical material for space observation camera of the STSAT-3. DOE (Design of Experiment) was used to find best machining characteristic for FPL-53. Finally we fabricated FPL-53 aspheric lens with the form accuracy of P-V $0.36\;{\mu}m$.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.218.2-218.2
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• 2012

In the remote sensing researches, the reflected bright source such as snow, cloud have effects on the image quality of wanted signal. Even though those signal from bright source are adjusted in corresponding pixel level with atmospheric correction algorithm or radiometric correction, those can be problem to the nearby signal as one of the stray light source. Especially, in the step and stare observational method which makes one mosaic image with several snap shots, one of target area can affect next to the other snap shot each other. Presented in this paper focused on the stray light analysis from unwanted reflected bright source for geostationary ocean color sensor. The stray light effect for total 16 slot images each other were performed according to 8 band filters. For the realistic simulation, we constructed system modeling with integrated ray tracing technique which realizes the same space time in the remote sensing observation among the Sun, the Earth, and the satellite. Computed stray light effect in the results of paper demonstrates the distinguishable radiance value at the specific time and space.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2001-2010
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• 2021

The purpose of this study is to efficiently improve orthorectification of KOMPSAT images. As the development of domestic and abroad earth observation satellites accelerates, the number and amounts of satellite images acquired are rapidly increasing. Accordingly, various studies are being conducted to improve orthorectification for the acquired image more quickly and efficiently. This study focused on enhancing processing efficiency through algorithm improvement, except for improving hardware computing capabilities such as GPU. Accordingly, the algorithm was improved with the LUT-based RFM method, and compared and analyzed in terms of accuracy and time-efficiency that vary depending on offset settings.

• Journal of Environmental Science International
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• v.26 no.5
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• pp.573-584
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• 2017

In order to simulate a typhoon precisely, the satellite observation data has been assimilated using WRF (Weather Research and Forecasting model) three-Dimensional Variational (3DVAR) data assimilation system. The observation data used in 3DVAR was GPS Radio Occultation (GPS-RO) data which is loaded on Low-Earth Orbit (LEO) satellite. The refractivity of Earth is deduced by temperature, pressure, and water vapor. GPS-RO data can be obtained with this refractivity when the satellite passes the limb position with respect to its original orbit. In this paper, two typhoon cases were simulated to examine the characteristics of data assimilation. One had been occurred in the Western Pacific from 16 to 25 October, 2015, and the other had affected Korean Peninsula from 22 to 29 August, 2012. In the simulation results, the typhoon track between background (BGR) and assimilation (3DV) run were significantly different when the track appeared to be rapidly change. The surface wind speed showed large difference for the long forecasting time because the GPS-RO data contained much information in the upper level, and it took a time to impact on the surface wind. Along with the modified typhoon track, the differences in the horizontal distribution of accumulated rain rate was remarkable with the range of -600~500 mm. During 7 days, we estimated the characteristics between daily assimilated simulation (3DV) and initial time assimilation (3DV_7). Because 3DV_7 demonstrated the accurate track of typhoon and its meteorological variables, the differences in two experiments have found to be insignificant. Using observed rain rate data at 79 surface observatories, the statistical analysis has been carried on for the evaluation of quantitative improvement. Although all experiments showed underestimated rain amount because of low model resolution (27 km), the reduced Mean Bias and Root-Mean-Square Error were found to be 2.92 mm and 4.53 mm, respectively.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.87-94
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• 2015

The increasing demands and utilization of the multi-purpose satellites have led to diverse research activities with regards to satellite image processing and applications. In the domestic development project for the Compact Advanced Satellite, it is a goal to develop the satellite with the domestic individual technique performing a various tasks such as the earth observation, the monitoring of the weather, climate and environment. In particular, the Compact Advanced Satellite is expect to be widely used in the agricultural sector, which account for a substantial part of public demand. This paper aims at establishing the way to utilize the satellite imagery in the domestic institution and the strategy for securing the specialized satellite payload in the agriculture sector. The technical element of satellite has a high value, so that it is hard to be transferred technology. For this reason, it is required to establish the domestic development planning. Furthermore, this paper can be utilized to identify and support the incoming Compact Advanced Satellite development plan utilizing satellite images capabilities specially in agricultural sector.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.10-14
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• 2016

Korean satellite development projects were divided military objectives such as national security, and commercial communication satellites. The First geostationary Korean earth observation satellite, GeoKOMPSAT is a turning point to concern another way to utilizing satellite. In the past, the main concern was the sharp ground images, now days, it is more important to make high added value from satellite data. In particular, environmental payload, GEMS mounted on the satellite GeoKOMPSAT-2 will monitor air quality which is not observed by visual material, may be referred to as case by utilizing the satellite. Satellite data utilization is likely to receive a great influence on the appropriate public policy data. If the public is expected to be fully revealed that potential demand. It is time to change the management policy on the security aspects of weak satellite data. Depending on the expanding use of satellites, it is necessary to investigate the status of disclosing satellite data, and suggests policy options for the distribution of materials for the environment satellite characteristics.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.441-444
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• 2005

The goal of this study is to investigate the relationship between microphytobenthic biomass and normalized vegetation index obtained from Landsat TM images. Monitoring a seasonal change of microphytobenthic biomass in the sand bar is specifically focused. Since the study area, Hampyeong Bay, was difficult to approach, we failed to obtain ground truths simultaneously on satellite image acquisition. Instead, chlorophyll-a concentration in surface top layer was measured on different dates for microphytobenthic biomass. Although data were acquired on different dates, a correlation between the field and satellite images was calculated for investigating general trends of seasonal change. NDVI and tasseled cap transformed images were also used to review the variation of microphytobenthic biomass by using Landsat TM and ETM+ images. Atmosphere effects were corrected by applying COST model. Seaweeds were also flouring in the same season of microphytobentic blooming. Songseok-ri area was minimally affected by seaweeds from February to May, and selected as a test site. NDVI value was classified into high-, moderate-, and low-grade. It was well developed over fme-grained sediments and rapidly reduced from May to November over sand bar. In this bay, correlation between grain size and microphytobenthic biomass was clearly seen. From the classified NDVI and tasseled cap transformed data, we finally constructed spatial distribution and seasonal variation maps of microphytobenthic biomass.