• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.436-439
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• 2004

Output data streams of the MSC contain flags, Headers and image data according to the established protocols and data formats. Especially the Header added to each data lines contain information of a line sync, a line counter and, ancillary data which consist of ancillary identification bit and one ancillary data byte. This information is used by ground station to calculate the geographic coordinates of the image and get the on-board time and several EOS(Electro-Optical Subsystem) parameters used at the time of imaging. Therefore, the EGSE(Electrical Ground Supporting Equipment) that is used for testing MSC has to have functions of interpreting and displaying this Header information correctly following the protocols. This paper describes the design of the header data processing module which is in EOS­EGSE. This module provides users with various test functions such as header validation, ancillary block validation, line-counter and In-line counter validation checks which allow convenient and fast test on imagery data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.73-76
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• 2007

For the space communication between a satellite and a ground station, spacecraft performs data packeting and data coding. Using standard format certainly has an advantage but depending on the hardware implementation sometimes compliance with the standard is hard to accomplish. This paper studies the suitable way to transfer image data and ancillary data to the ground station in the format of CCSDS recommendation.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.31-35
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• 2002

This paper describes an experiment for three-dimensional positioning for a pair of KOMPSAT stereostrips using the ancillary data and a single ground control point. The photogrammetric model for three-dimensional positioning was performed as follows: first, initialization of orbital and attitude parameters derived from ancillary data; second, adjustment of orbital and attitude parameters for the satellite to minimize the ground position error with respect to a GCP using the collinearity condition; third, determination of actual satellite position; and lastly, space intersection. This model was tested for a pair of stereo strips with 0.6 base-to-height ratio and GCPs identified from a 1:5,000 scale digital map. As the result, the satellite position of offset was corrected by only one GCP and the accuracy for the geometric modeling showed 38.89m RMSE.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• Korean Journal of Organic Agriculture
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• v.15 no.4
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• pp.355-376
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• 2007

This study evaluated economic feasibility to find a method that can increase income of a rape farmer for biodiesel. Biodiesel is one of an important bioenergy that can be used to substitute diesel-fuel. A rape is useful not only for biodiesel, but also for a substitute of a barley. This study deals with the income and cost data of a rape farmer compare to that of a barley farmer. According to the result of economic evaluation from 2002 to 2006, the income of a rape farmer for biodiesel incurred a loss. However, this study showed that the income of a rape farmer would be approximately 80% of that of a barley farmer if a new variety of rape called 'SUNMANG' was growed. Also, biodiesel has various ancillary effects such as by-product, preservation of a scenery, reduction of $CO_2$, etc. If the income of a rape farmer had ancillary effects, it would exceed the income of a barley farmer. As a result, we need to support ancillary effects of a rape to encourage a rape farmer for biodiesel.

• Korean Journal of Organic Agriculture
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• v.14 no.3
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• pp.237-249
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• 2006

The objective of this paper was to evaluate economic feasibility of biodiesel production. Biodiesel is a diesel-fuel replacement produced from domestic renewable resources such as vegetable oils. This paper deals mainly with the income and cost data to analyze economic feasibility of biodiesel. The income of a rape farmer for biodiesel was 206,894won/10a, and it's similar to barley income. In addition a rape production for biodiesel have ancillary effect. Therefore we have to use direct payment for encouraging the production and use of biodiesel.

• Aerospace Engineering and Technology
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• v.1 no.2
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• pp.141-148
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• 2002

The purpose of this study is to enhance geo-location accuracy of the image data acquired by the Electro-Optical Camera(EOC) onboard KOMPSAT-1. EOC image data were analyzed to verify geo-location error. It was found that the major contribution was the time mark inaccuracy and attitude knowledge error. This study shows that the geo-location accuracy can be enhanced by modifying the time and attitude data of the ancillary data.

• Atmosphere
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• v.29 no.4
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• pp.355-365
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• 2019

Based on in-situ monitoring data produced by National Institute of Meteorological Sciences, we evaluated the performance of Joint UK Land Environment Simulator (JULES) on the surface energy balance for rice-paddy and cropland in Korea with the operational ancillary data used for Unified Model (UM) Local Data Assimilation and Prediction System (LDAPS) (CTL) and the high-resolution ancillary data from external sources (EXP). For these experiments, we employed the one-year (March 2015~February 2016) observations of eddy-covariance fluxes and soil moisture contents from a double-cropping rice-paddy in BoSeong and a cropland in AnDong. On the rice-paddy site the model performed better in the CTL experiment except for the sensible heat flux, and the latent heat flux was underestimated in both of experiments which can be inferred that the model represents flood-irrigated surface poorly. On the cropland site the model performance of the EXP experiment was worse than that of CTL experiment related to unrealistic surface type fractions. The pattern of the modeled soil moisture was similar to the observation but more variable in time. Our results shed a light on that 1) the improvement of land scheme for the flood-irrigated rice-paddy and 2) the construction of appropriate high-resolution ancillary data should be considered in the future research.

• Journal of Korea Water Resources Association
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• v.37 no.1
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• pp.21-29
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• 2004

The growth of water resources engineering associated with stable supply, management, development is essential to overcome the coming water deficit of our country. Large scale remote sensing and the analysis of sub-pixel variability of soil moisture fields are necessary in order to understand water cycle and to develop appropriate hydrologic model. The target resolution of coming Global monitoring of soil moisture field is about 10km which is not appropriate for the regional scale hydrologic model. Therefore, we need a downscaling scheme to generate hydrologic variables which are suitable for the regional hydrologic model. The results of the analysis of sub-pixel soil moisture variability show that the relationship between ancillary data and soil moisture fields shows there is very weak linear relationship. A downscaling scheme was developed using physically-based classification scheme and Neural Networks which are able to link the nonlinear relationship between ancillary data and soil moisture fields. The model is demonstrated by downscaling soil moisture fields from 4km to 0.2km resolution using remotely-sensed data from the Washita'92 experiment.

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.21-35
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• 1996

In this paper, estimation and prediction procedures are discussed for grneral situation in which the failure time follows the independent density $f_{i}({\varepsilon}_{i})$ for the accelerated life testing under Type II censoring. In the context of accelerated life test experiment, procedures are given for estimating the parameters in the Eyring model, and for estimating mean life at a given future stress level. The procedures given are conditional confidence interval procedures, obtained by conditioning on ancillary statistics. A comparison is made of these procedures and procedures based on asymptotic properties of the maximum, likelihood estimates.