• 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.

• Journal of Astronomy and Space Sciences
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• v.32 no.3
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• pp.229-235
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• 2015

We estimated the orbit of the Communication, Ocean and Meteorological Satellite (COMS), a Geostationary Earth Orbit (GEO) satellite, through data from actual optical observations using telescopes at the Sobaeksan Optical Astronomy Observatory (SOAO) of the Korea Astronomy and Space Science Institute (KASI), Optical Wide field Patrol (OWL) at KASI, and the Chungbuk National University Observatory (CNUO) from August 1, 2014, to January 13, 2015. The astrometric data of the satellite were extracted from the World Coordinate System (WCS) in the obtained images, and geometrically distorted errors were corrected. To handle the optically observed data, corrections were made for the observation time, light-travel time delay, shutter speed delay, and aberration. For final product, the sequential filter within the Orbit Determination Tool Kit (ODTK) was used for orbit estimation based on the results of optical observation. In addition, a comparative analysis was conducted between the precise orbit from the ephemeris of the COMS maintained by the satellite operator and the results of orbit estimation using optical observation. The orbits estimated in simulation agree with those estimated with actual optical observation data. The error in the results using optical observation data decreased with increasing number of observatories. Our results are useful for optimizing observation data for orbit estimation.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.673-678
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• 2002

A satellite remote sensing is useful for vegetation monitoring. But it has some problem. One of these, it is difficult to find a difference of vegetation surface roughness using satellite remote sensing. Each vegetation type has unique surface roughness, for example needle leaves forest, broad leaves forest and grassland. Difference of vegetation surface roughness can be detected by satellite multiangular observation. In this study, objective is to propose index of vegetation surface roughness using BRF property. General vegetation indices are calculated from nadir data of satellite data. A proposed index is calculated from two different observation zenith angle data. Two different zenith data can provide BRF (Bi-directional Reflectance Factor) property of satellite observation data. A proposed index was able to detect different value on where NDVI shows similar high value areas of rice field and forest. This index is useful for vegetation monitoring.

• Journal of Astronomy and Space Sciences
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• v.32 no.3
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• pp.221-228
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• 2015

To protect and manage the Korean space assets including satellites, it is important to have precise positions and orbit information of each space objects. While Korea currently lacks optical observatories dedicated to satellite tracking, the Korea Astronomy and Space Science Institute (KASI) is planning to establish an optical observatory for the active generation of space information. However, due to geopolitical reasons, it is difficult to acquire an adequately sufficient number of optical satellite observatories in Korea. Against this backdrop, this study examined the possible locations for such observatories, and performed simulations to determine the differences in precision of optical orbit estimation results in relation to the relative baseline distance between observatories. To simulate more realistic conditions of optical observation, white noise was introduced to generate observation data, which was then used to investigate the effects of baseline distance between optical observatories and the simulated white noise. We generated the optical observations with white noise to simulate the actual observation, estimated the orbits with several combinations of observation data from the observatories of various baseline differences, and compared the estimated orbits to check the improvement of precision. As a result, the effect of the baseline distance in combined optical GEO satellite observation is obvious but small compared to the observation resolution limit of optical GEO observation.

• Proceedings of the KSRS Conference
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• v.1
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• pp.228-231
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• 2006

In this paper, requirements of Meteorological Administration about Meteorological Imager (MI) of Communications, Ocean and Meteorological Satellite (COMS) is analyzed for the design of COMS ground station and according to the analysis results, the distribution image size of each observation area suitable for satellite Field Of View (FOV) stated at the requirements of meteorological administration is determined and the precise satellite FOV and the size of distribution image is calculated on the basis of the image size of the determined observation area. The results in this paper were applied to the detailed design for COMS ground station and also are expected to be used for the future observation scheduling and the scheduling of distribution of user data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.349-352
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• 2007

The Fourth Assessment Report of IPCC predicted that global warming is already happening and it should be caused from the increase of greenhouse gases by the extension of human activities. These global changes will give a serious influence for human society. Global environment can be monitored by the earth observation using satellite. For the observation of global climate change and resolving the global warming process, satellite should be useful equipment and its detecting data contribute to social benefits effectively. JAXA (former NASDA) has made a new plan of the Global Change Observation Mission (GCOM) for monitoring of global environmental change. SGLI (Second Generation GLI) onboard GCOM-C (Climate) satellite, which is one of this mission, provides an optical sensor from Near-DV to TIR. Characteristic specifications of SGLI are as follows; 1) 250 m resolutions over land and area along the shore, 2) Three directional polarization observation (red and NIR), and 3) 500 m resolutions temperature over land and area along shore. These characteristics are useful in many fields of social benefits. For example, multi-angular observation and 250 m high frequency observation give new knowledge in monitoring of land vegetation. It is expected that land products with land aerosol information by polarization observation are improved remarkably. We are studying these possibilities by ground data and satellite data.

• Atmosphere
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• v.32 no.4
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• pp.263-276
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• 2022

The observation error of satellite radiation data that assimilated into the Korean Integrated Model (KIM) was diagnosed by applying the Hollingsworth and Lönnberg and Desrozier techniques commonly used. The magnitude and correlation of the observation error, and the degree of contribution for the satellite radiance data were calculated. The observation errors of the similar device, such as Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit-A shows different characteristics. The model resolution accounts for only 1% of the observation error, and seasonal variation is not significant factor, either. The observation error used in the KIM is amplified by 3-8 times compared to the diagnosed value or standard deviation of first-guess departures. The new inflation value was calculated based on the correlation between channels and the ratio of background error and observation error. As a result of performing the model sensitivity evaluation by applying the newly inflated observation error of ATMS, the error of temperature and water vapor analysis field were decreased. And temperature and water vapor forecast field have been significantly improved, so the accuracy of precipitation prediction has also been increased by 1.7% on average in Asia especially.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.368-368
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• 2008

Oil spills are a principal factor of the ocean pollution. The complicated problems involved in detecting oil spills are usually due to varying wind and sea surface condition such as ocean wave and current. The Hebei Spirit accident was happened in the west sea ($36^{\circ}$41'04" N, $126^{\circ}$03'12" E) near about 8 km distant from Tae-An, Korea on December 7, 2007. The aim of this work is to improve the detection and classification performance in order to define a more accurate training set and identifying the feature of oil spill region. This paper deals with an optimization technique for the detection and classification scheme using multi-frequency and multi-polarization SAR and optical image data sets of the oil spilled sea. The used image data are the ENVISAT ASAR WS and Radarsat-1 of C-band and ALOS PALSAR of L-band SAR data and KOMPSAT-2 optical images together with meteorological or oceanographic data. Both the theory and the experimental results obtained are discussed.

• Current Industrial and Technological Trends in Aerospace
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• v.9 no.1
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• pp.45-54
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• 2011

Earth observation satellites data apply to various fields and global satellite imagery market continues to expand with increasing the scale according to the developed satellites. Sudden natural disasters frequently have occurred in Japan. ALOS satellite data support to repair the damaged area and mitigate the disasters in Japan as well as all around the world. In this paper, the status of remote sensing and data policy in Japan are described. In addition, satellite-based remote sensing technology effectively contribute to the public sector and related support to establish the infra system of satellite application promotion has been investigated.