• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.293-300
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• 1999

The study aims to develope techniques for generating digital elevation model(DEM) from IRS-1C PAN stereo image data. The bundle adjustment technique was used to determine the satellite exterior orientation parameters as a function of along-track lines. The first degree of polynomial was selected as a function of satellite attitude and position for each scan line. To evaluate the DEM and orthoimage generated, the resulted three dimensional coordinates of the 16 elevation points were computed with the map coordinates. The elevation test showed that root mean square errors of the DEM elevation was about $\pm{16.66m}$ meters.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.13-18
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• 2019

The DEM(Digital Elevation Model) is a three-dimensional spatial information that stores the height of the terrain as a numerical value. This means the elevation of the terrain not including the vegetation and the artifacts. The DEM is used in various fields, such as 3D visualization of the terrain, slope, and incense analysis, and calculation of the quantity of construction work. Recently, many studies related to the construction of 3D geospatial information have been conducted, but research related to DEM generation is insufficient. Therefore, in this study, a DEM was constructed using a MMS (Mobile Mapping System), UAV image, and UAV LiDAR (Light Detection And Ranging), and the accuracy evaluation of each result was performed. As a result, the accuracy of the DEM generated by MMS and UAV LiDAR was within ± 4.1cm, and the accuracy of the DEM using the UAV image was ± 8.5cm. The characteristics of MMS, UAV image, and UAV LiDAR are presented through a comparison of data processing and results. The DEM construction using MMS and UAV can be applied to various fields, such as an analysis and visualization of the terrain, collection of basic data for construction work, and service using spatial information. Moreover, the efficiency of the related work can be improved greatly.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.41-50
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• 2008

Recent progress in state-of-the-art geospatial information technologies such as digital mapping, LiDAR(Light Detection And Ranging), and high-resolution satellite imagery provides various data sources fer Digital Elevation Model(DEM). DEMs are major source to extract elements of the hydrological terrain property that are necessary for efficient watershed management. Especially, watersheds extracted from DEM are important geospatial database to identify physical boundaries that are utilized in water resource management plan including water environmental survey, pollutant investigation, polluted/wasteload/pollution load allocation estimation, and water quality modeling. Most of the previous studies related with watershed extraction using DEM are mainly focused on the hydrological elements analysis and preprocessing without considering grid size of the DEMs. This study aims to analyze accuracy of the watersheds extracted from DEMs with various grid sizes generated by LiDAR data and digital map, and appropriate preprocessing methods.

• Spatial Information Research
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• v.10 no.3
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• pp.439-453
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• 2002

Researches using DEM are actively progressed in field of water resource, and especially the extraction of watershed and stream based on topographic and hydrologic analysis, is widely used in GIS analysis recently. However, because it is extracted that watershed which is type of sliver polygon and stream which is type of straight line in low topographic region, they're not efficient for application. This study determined buffer zone from stream and tried smooth elevation change to buffer zone in order to efficiently extract abnormal watershed and stream being occurred in low topographic region. Especially, we applied equal-distance assignment model using Voronoi Diagram to determine smooth elevation change. Also, we extracted watershed and stream using stream recognition DEM and origional DEM, and evaluated the efficiency of research through comparing the shape of watershed and stream in low topographic region.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.1-9
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• 1990

This paper presents a method of the constructing DEM(Digital Elevation Model) from the image data acquired from a commercial map using the scanner. Data acquistion, mark elimination, linking the broken line, elevation interpolation and 3D display processing are performed and the results are satisfatory.

• Journal of the Korean Society of Safety
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• v.24 no.6
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• pp.1-6
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• 2009

This study describes a construction procedure of 3D virtual space using the NGIS data and its application to simulation. 3D space topography is modeled by using DEM consisted with triangular regular network. The elevations of nodal points of DEM are calculated through the interpolation with contour line and elevation points from the NGIS. Also, data for 2D roads and their environments, such as trees, lamps, and traffic signals, were extracted from the NGIS and projected on the DEM surfaces to get 3D virtual space. To give a reality to 3D virtual space and accelerate its graphic speed, data were converted into the directX format. It is believed that the virtual space constructed in this work can be applicable to the ubiqutous because DEM data can be converted to the AutoCAD format and ASCII code.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.1
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• pp.22-31
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• 2001

The purpose of this study is to compare calculated pollutant loadings using pollutant load unit factors and vector type coverage, and expected mean concentration(EMC) and raster type of digital elevation model(DEM). This study is also focusing on comparison of the advantages and the disadvantages of the two methods, and seeking for a method of calculation of pollutant loadings using DEM. Estimation of pollutant inputs using pollutant load unit factors has limitations in identifying seasonal variations of pollutant loadings. Seasonal changes of runoffs should be considered in the calculation of pollutant loadings from catchments into reservoirs. Evaluation of pollutant inputs using runoff-coefficient and EMC can overcome these drawbacks. Proper EMC and runoff-coefficient values for the Koeup stream catchments of the Koheung estuarine lake were drawn from review of related papers. Arc/Info was employed to establish database of spatial and attribute data of point and non-point pollutant sources and characteristics of the catchments. ArcView was used to calculate point and non-point pollutant loadings. Pollutant loads estimated with either unit factors-coverages, i.e., pollutant load unit factors and vector coverages f point sources and land use, or EMC and digital elevation mode(DEM) were compared with stream monitoring loads. We have found that some differences were shown between monitoring results and estimated loads by Unit Factors-Coverage and EMC-DEM. Monthly variations of pollutant loads evaluated with EMC-DEM were similar to those with monitoring result. The method using EMC-DEM can calculate accumulated flows and pollutant loads and can be utilized to identify stream networks. A future research on correcting the difference between vector type stream using flow direction grid and digitalizing vector type should be conducted in order to obtain more exact calculation of pollutant loadings.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2005.11a
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• pp.59-80
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• 2005

This Paper Presents a Rational Function Model (RFM)-based image matching technique for IKONOS satellite imagery. This algorithm adopts the object-space approach and reduces the search space within the confined line-shaped area called the Piecewise Matching Line (PLM). Also, the detailed procedure of generating 3-D surface information using the Rational Function model Coefficients (RFCs) is introduced as an end-user point of view. As a result, the final generated Digital Elevation Model (DEM) using the proposed scheme shows a mean error of 2$\cdot$2 m and RMSE of 3$\cdot$8 m compared with that from 1:5000 digital map.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.439-450
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• 2018

The lineament is a linear or curved terrain element to discriminate adjacent geological structures in each other. It has been widely used for analysis of geology, mineral exploration, natural disasters, and earthquake, etc. In the past, the lineament has been extracted using cartographic map or field survey. However, it is possible to extract more efficiently the lineament for a very wide area thanks to development of remote sensing technique. Remotely sensed observation by aircraft, satellite, or digital elevation model (DEM) has been used for visual recognition for manual lineament extraction. Automatic approaches using computer science have been proposed to extract lineament more objectively. In this study, we evaluate the characteristics of lineament which is automatically extracted with respect to difference of spatial resolution of DEM. We utilized two types of DEM: one is Shuttle Radar Topography Mission (SRTM) with spatial resolution of about 90 m (3 arc sec), and the other is the latest world DEM of TerraSAR-X add-on for Global DEM with 12 m spatial resolution. In addition, a global DEM was resampled to produce a DEM with a spatial resolution of 30 m (1 arc sec). The shaded relief map was constructed considering various sun elevation and solar azimuth angle. In order to extract lineament automatically, we used the LINE module in PCI Geomatica software. We found that predominant direction of the extracted lineament is about $N15-25^{\circ}E$ (NNE), regardless of spatial resolution of DEM. However, more fine and detailed lineament were extracted using higher spatial resolution of DEM. The result shows that the lineament density is proportional to the spatial resolution of DEM. Thus, the DEM with appropriate spatial resolution should be selected according to the purpose of the study.