• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.3
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• pp.291-300
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• 2001

In this paper, we developed a Satellite Image Processing System for obtaining 3-D positional information which is composed of five process modules. As a procedure of them, the Data Process module is the procedure that reads and processes the header file to generate data files. and then calculates orbital parameters and sensor attitudes for obtaining of 3-D positional information with them. The 3D Process module is to calculate 3-D positional information and the Dialog Process module is to correct the time of image frame center using the single image or stereo images for implementing the 3D Process module. We expect to obtain 3-D positional information with the header file and minimum GCPs(1∼2 points) using this system efficiently and economically in comparison with existing commercial software packages.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.289-297
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• 2006

The Land Cover/Land Use Map have been constructed from 1998, which has hierarchical structure according to land cover/land use system. Level 1 classification Map have done using Landsat satellite image over whole Korean peninsula. Level II classification Map have been digitized using IRS-1C, 1D, KOMPSAT and SPOT5 satellite images resolution-merged with low resolution color images. Level II Land Cover/Land Use Map construction by digitizing method, however, is consuming enormous expense for satellite image acquisition, image process and Land Cover/Land Use Map construction. In this paper, the possibility of constructing Level II Land Cover/Land Use Map using hyperspectral satellite image of EO-1 Hyperion, which is studied a lot recently, is studied. The comparison of classifications using Hyperion satellite image offering more spectral information and Landsat-7 ETM+ image is performed to evaluate the availability of Hyperion satellite image. Also, the algorithm of the optimal band selection is presented for effective application of hyperspectral satellite image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.359-365
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• 2008

This paper focused on generation of more accurate DEM and analysis of accuracy. For this, we applied suitable sensor modeling technique for each satellite image and automatic pyramid matching using image pyramid was applied. Matching algorithm based on epipolarity and scene geometry also was applied for stereo matching. IKONOS, Quickbird, SPOT-5, Kompsat-2 were used for experiments. In particular, we applied orbit-attitude sensor modeling technique for Kompsat-2 and performed DEM generation successfully. All DEM generated show good quality. Assessment was carried out using USGS DTED and we also compared between DEM generated in this research and DEM generated from common software. All DEM had $9m{\sim}12m$ Mean Absolute Error and $13m{\sim}16m$ RMS Error. Experimental results show that the DEMs of good performance which is similar to or better than result of DEMs generated from common software.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.173-178
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• 2004

This paper presents photogrammetric processing to generate digital elevation models and deals with the accuracy potential of SPOT-5 HRG supermode imagery for DEM generation. The DEMs obtained from digital topographic maps of 1/5000 scale were used as the refernce DEM data. DEMs extracted from HRG dats were compared with digital topograpic map DEMs on severed test sections. And digital surface model(DSM), refering to above the ground like buildings, was produced about the test built-up area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.1
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• pp.89-96
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• 2005

With acquisition of satellite image being facilitated due to recent advancement in Electro optical and astronautic technologies, focus on establishment of Geoinformation and analysis using satellite images have increased. This research have conducted digital plotting and digitizing operation, utilizing stereo images and grey level images provided by SPOT5 satellite and evaluated the accuracy through comparison and analysis with digital map results. Digital plotting results acquired using stereo images have been compared and analyzed on the basis of scale 1:25,000 digital map results published by National Geographic Information Institute. Accuracy of 20 check points have showed RMSE results 5.369 m at X (Easting) and 4.718 m, digitizing using grey level images showed RMSE results 7.616 m in X (Easting) and Y (Northing) 6.532 m. This is within the allowance of accuracy standards for scale 1:25,000 maps, and although digitizing operation was confirmed to have lower accuracy than that of digital plotting, using the former is considered to be more effective in terms of economical efficiency.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.195-208
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• 1999

In the classification of satellite images, the representative of training of classes is very important factor that affects the classification accuracy. Hence, in order to improve the classification accuracy, it is required to optimize pre-classification stage which determines classification parameters rather than to develop classifiers alone. In this study, the normality of training are calculated at the preclassification stage using SPOT XS and LANDSAT TM. A correlation coefficient of multivariate Q-Q plot with 5% significance level and a variance of initial training are considered as an object function of genetic algorithm in the training normalization process. As a result of normalization of training using the genetic algorithm, it was proved that, for the study area, the mean and variance of each class shifted to the population, and the result showed the possibility of prediction of the distribution of each class.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.465-474
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• 2009

To measure the amount of nonpoint source pollution, some efforts are tried to utilize satellite imagery. But, as the factors for water models do not relate with the landcover categories for satellite imagery, satellite imagery are adapted to roughly classified thematic map or used only for the image interpretation. The purpose of this study is to establish the landcover categories of satellite imagery to relate with the water models. To establish the categories of the landcover for the water models, it was investigated to get main factors of water flow models for the nonpoint source pollution and to review the existing study and the classification system. For this result, it was convinced that the basic unit on the nonpoint source pollution, landcover coefficients of SCS Curve Number, the crop factor of Universal Soil Loss Equation, Manning's roughness coefficients are the useful parameters to extract information from the satellite imagery. After the setup the categories for the landcover classification, it was finally defined from the consultation of the water model specialist. Woopo wetland watershed was selected to the study area because it is a representative wetland in Korea and needs the management system for nonpoint source pollution. There were used Landsat ETM Plus and SPOT-5 satellite imagery to assess the result of the image classification.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.33-44
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• 2001

The paper presents several satellite models and satellite image decomposition methods for inaccessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in $1^{st}$, $2^{nd}$ and $3^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\Phi$(phi) correlated highly with positional parameters could be assigned to constant values. For inaccessible area, satellite images were decomposed, which means that two consecutive images were combined as one image, The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1st order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.140-148
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• 2001

The satellite sensor model is typically established using ground control points acquired by ground survey Of existing topographic maps. In some cases where the targeted area can't be accessed and the topographic maps are not available, it is difficult to obtain ground control points so that geospatial information could not be obtained from satellite image. The paper presents several satellite sensor models and satellite image decomposition methods for non-accessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then the behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in 1$^{st}$, 2$^{nd}$ and 3$^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\phi$(phi) correlated highly with positional parameters could be assigned to constant values. For non-accessible area, satellite images were decomposed, which means that two consecutive images were combined as one image. The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1$^{st}$ order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1787-1792
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• 2005

The join of remote sensing and GIS(Geographic Information System) could be useful in various fields of marine information and land information as well as ITS(Intelligent Transport Systems). This paper is LPF(Low Pass Filtering) for the extraction of island detection in coastal zone Iron SPOT imagery which is 10m resolution photograph. The study area is based on the southern sea in korea. Sobel operator performed the extraction of island detection in coastal zone after the LPF processing by remote sensing. And, GIS was used to generate from raster to vector data. As the result, The best way prove out the 5${\times}$5 convolution mask about the LPF processing of island detection in coastal zone. It is judged the research which it sees with the fact that the presentation of very scientific and reasonable data will be possible from the oceanic dispute will occur from the EEZ(Exclusive Economic Zone).