• 한국지형공간정보학회:학술대회논문집
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• 1995.10a
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• pp.99-119
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• 1995

Most studies using satellite images have been performed to determine three dimensional positioning by stereoscopic analysis for stereo-pair or to extract digital elevation model by stereo matching using image correlation techniques. Because the small errors on the ground control points have a great impact on the results, honorer, it is hard to get reliable products when we analyze satellite orbital parameters or acquire digital elevation model by using only stereo-pair. Also, if there are noises, shadows, or clouds on the one of stereo pair, it is difficult to produce DEM(digital elevation model) on the area under analysis or to have good accuracy. In these case, it can be solved by systematic analysis of the multiple stereo images. This paper suggests the improvements on the accuracy of the digital elevation model by the developments of stereoscopic analysis techniques for the triplet of SPOT satellite images on the same area.

• The Journal of Engineering Geology
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• v.2 no.2
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• pp.141-146
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• 1992

Synthetic stereo-pair of Landsat TM(Thematic Mapper) and shaded relief image from DEM(Digital Elevation Model) were digitally produced. They are very useful in optimizing the geological interpretability of the remotely sensed data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.182-182
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• 2003

Generally, DEM (Digital Elevation Model) is generated by stereo-images acquired same conditions, sensor type, viewing angle, capturing elevation and etc. It is difficult to generate DEM with stereo images acquired different satellite. This study intends that it is DEM generation using pair-images with other sensor systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.223-235
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• 2020

In this study, we propose an approach for calibrating the elevation of a DEM (Digital Elevation Model), one of the key data in realizing unmanned aerial vehicle image-based precision agriculture. First of all, radiometric correction is performed on the orthophoto, and then ExG (Excess Green) is generated. The non-vegetation area is extracted based on the threshold value estimated by applying the Otsu method to ExG. Subsequently, the elevation of the DEM corresponding to the location of the non-vegetation area is extracted as EIFs (Elevation Invariant Features), which is data for elevation correction. The normalized Z-score is estimated based on the difference between the extracted EIFs to eliminate the outliers. Then, by constructing a linear regression model and correcting the elevation of the DEM, high-quality DEM is produced without GCPs (Ground Control Points). To verify the proposed method using a total of 10 DEMs, the maximum/minimum value, average/standard deviation before and after elevation correction were compared and analyzed. In addition, as a result of estimating the RMSE (Root Mean Square Error) by selecting the checkpoints, an average RMSE was derivsed as 0.35m. Comprehensively, it was confirmed that a high-quality DEM could be produced without GCPs.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.121-132
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• 1997

This paper describes the development of a stereo matching algorithm for extracting Digital Elevation Model(DEM) from satellite images. This matching algorithm is based on a non-linear least squares correlation estimation but has improved matching speed. The algorithm consists of three steps: matching execution, matching control and matching optimization. Each is described. The performance of the presented algorithm is quantitatively analyzed with experiments on matching probability, matching speed and matching convergence radius.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.155-164
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• 2001

In this study, we describe the technique for deriving a digital elevation model (DEM) from a synthetic aperture radar (SAR) stereo image pair and apply it to an image pair over "Kwanak-san" in Seoul, Korea. This paper contains brief discussion of the use of stereo SAR to derive topographic data, description of the overall structure of the stereo SAR processing system, description of the site and SAR data used for the evaluation and the source of validation data, results of the stereo SAR processing, analysis and evaluation of their accuracy against map data, and finally summarizes the main highlights of the method used, comments and recommendations on its future implementation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.10 no.2
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• pp.49-55
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• 1992

Sampling techniques is very important in digital elevation model. There are scanning and digitizing method of sampling techniques. This study is limited in digitizing method. Continous sampling method use contour lines as same entity and grid method is a direct reading of sample elevation in each grid. Triangulated irregular method is needed to identity topographical lines to sample elevation data. As a results, authors know that continous sampling method has economic in input system and triangulated irregular method has a small memory size.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.342-348
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• 1998

The purpose of this paper is to extract fast DEM (Digital Elevation Model) using satellite images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding poults of them and third part is to calculate the elevation of each point by using the result of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. A area based matching method is used to find corresponding points between the stereo satellite images. In the DEM generation system, this procedure holds most of a processing time, therefore a new fast matching algorithm is proposed to reduce the time for matching. The elevation of each point is calculated using the exterior orientation obtained from modeling and disparity from matching. In this paper, the SPOT satellite images, level IA 6000 $\times$6000 panchromatic images are used to extract DEM. The experiment result shows the possibility of fast DEM. extraction with the satellite images.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.347-353
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• 2000

The purpose of this paper is to extract DEM (Digital Elevation Model) using KOMPSAT images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the result of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. Area based matching method is used to find the corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation information obtained from sensor modeling and the disparity from the stereo matching. In experiment, the KOMPSAT images, 2592$\times$2796 panchromatic images are used to extract DEM. The experiment result show the DEM using KOMPSAT images.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.177-188
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• 2000

Quantitative accuracy assessment of a SPOT DEM (Digital Elevation Model) generated by a fully automatic software is performed along the 90km long coast around Donghae city. The theoretical requirement on the layout of the CPS (Global Positioning System) check points is derived: the Nyquist sampling. Since in practice the Nyquist frequency of a terrain is difficult to determine, the relaxed requirements are introduced and 31 check points are collected accordingly. Accuracy of the SPOT DEM is calculated to be 8.9, 11.5 and 12.0m r.m.s. in latitudinal, longitudinal and elevation directions. The bias is distinguishable from zero only for elevation and is 2.2m. The simple comparison with the world's leading commercial softwares reveals the similar accuracy level.