• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.3-7
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• 1998

The issue of data accuracy brings a different perspective to the issue of GIS modeling, calls into a question the usefulness of data models such as DEM. Accuracy can be determined by randomly checking positional and attribute accuracy within a GIS data layer. With the increasing availability of DEM and the software capable of processing them, it is worthwhile to call attention for data accuracy and error analysis as GIS application depends on the priori established spatial data. The purpose of this paper was to investigate methods for data accuracy measurement and error detection methodology with two types of DEM's: 1 to 24,000 and 1 to 250,000 DEM released by U.S. Geological Survey. Another emphasis was given to the development of methodology for processing DEM's to create Arc/Info and GRASS layers. Data accuracy analysis with DEM was applied to a 250 sq.km area and an error was detected at a scale of 1:24,000 DEM. There were two possible reasons for this error: gross errors and blunders.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.80-83
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• 1999

An efficient modeling and management of a large amount of surface data for a wide rage of geographic information play an important role in determining the functionality of 3D geographic information system. It has been put many efforts to design and manage an effective way to enhence the manipulation of the data by considering geometry type and data structures. Recently, DEM(Data Elevation Model) and TIN(Triangulated Irregular Network) are used for representing surface data. In this paper, we propose a 3D data processing method. The method utilizes the major properties of DEM and TIN, respectively. Furthermore, by approximating DEM with a TIN of an appropriate resolution, we can support a fast and realistic surface modeling. We implement the structure with the following 4 level stages. The first is an optimal resolution of DEM which represent all of wide range of geographic data. The second is the full resolution DEM which is a subarea of original data generated by user's selection in our implemeatation. The third is the TIN approximation of this data with a proper resolution determined by the relative position with the camera. And the last step is multi-resolution TIN data whose resolution is dynamically decided by considering which direction user take notice currently. Specially, the TIN of the last step is designed for realtime camera navigation. By using the structure we implemented realtime surface clipping, efficient approximation of height field and the locally detailed surface LOD(Level of Detail). We used the initial 10-meter sampling DEM data of Seoul, KOREA and implement the structure to the 3D Virtual GIS based on the Internet.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.142-145
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• 2005

As SAR data have the strong point that is not influenced by weather or light amount compared with optical sensor data, they have high usfulness as temporary analysis fast and can be collected in case of like disaster. This study is to extract DEM from L-band data of JERS-1 SAR imagery using InSAR and DInSAR processing techniques. The accuracies of DEM extracted from the SAR data were evaluated by employing DEM derived from the digital topographic maps of 1:5000 scale as standard data.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.66-71
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• 1999

For given 3D geographic data which is usually of DEM(Data Elevation Model) format, we have to represent and manipulate the data in various ways. For example, we have to draw a part of them in drawing canvas. To do this we give users a way of selecting area they want to visualize. And we have to give a base tool for users to select the local area which can be chosen for some geographic operation. In this paper, we propose a 3D data processing method for representation and manipulation. The method utilizes the major properties of DEM and TIN(Triangular Irregular Network), respectively. Furthermore, by approximating DEM with a TIN of an appropriate resolution, we can support a fast and realistic surface modeling. We implement the structure with the following 4 level stages. The first is an optimal resolution of DEM which represent all of wide range of geographic data. The second is the full resolution DEM which is a subarea of original data generated by user's selection in our implemeatation. The third is the TIN approximation of this data with a proper resolution determined by the relative position with the camera. And the last step is multi-resolution TIN data whose resolution is dynamically decided by considering which direction user take notice currently. Specialty, the TIN of the last step is designed for realtime camera navigation. By using the structure we implemented realtime surface clipping, efficient approximation of height field and the locally detailed surface LOD(Level of Detail). We used the initial 10-meter sampling DEM data of Seoul, KOREA and implement the structure to the 3D Virtual GIS based on the Internet.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.61-66
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• 2009

This Paper describes a new program called DEM Generator need to process DEM from LiDAR data or digital map data. It is difficult to generate raster DEM from LiDAR mass point data sets and digital maps too large to fit into memory. The DEM Generator was designed to process DEM and shaded relief image of GeoTiff format in order of streaming meshes; I/O minimize tag, delaunay triangle, natural neighborhood or TIN, temporary files and grid. It is expected that we can be improved the precision of DEM and solved the time consuming problem of DEM generating of a wider area.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.176-186
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• 2007

As SAR data have the strong point that is not influenced by weather or light amount in comparison with optical sensor data, they are highly useful for temporary analysis and can be collected in time of unforeseen circumstances like disaster. This study is to extract DEM from L-band data of JERS-1 SAR imagery using InSAR and DInSAR processing techniques. As a result of analyzing the extracted coherence and interferogram images, it was shown that the DInSAR 3-pass method produces more suitable coherence values than the InSAR method. The accuracies of DEM extracted from the SAR data were evaluated by employing the DEM derived from the digital topographic maps of 1:5000 scale as reference data. And it was ascertained that baselines between antenna locations largely affect the accuracy of extracted DEM.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.512-514
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• 2005

Accurate DEM surface of forest floor is very important to extract any meaningful information regarding forest stand structure, such as tree heights, stand density, crown morphology, and biomass. In airborne lidar data processing, DEM data of forest floor is mostly generated by interpolating those elevation points obtained from last laser returns. In this study, we try to analyze the property of the last laser return under relatively dense forest canopy. Airborne laser data were obtained over the study area in relatively dense pine plantation forest. Two DEM data were generated by using all the points in the last laser returns and using only those points after removing non-ground points. From the preliminary analysis on these DEM data, we found that more than half of points among the last laser returns are actually hit from canopy, branches, and understory vegetation that should be removed before generating the surface DEM data.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.453-456
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• 2002

In this study, the effect of DEM resolution (15m, 30m, 50m, 70m, 100m, 200m, 300m) on the hydrological simulation was examined using BASINS (Better Assessment Science Integrating point and Nonpoint Source) for Heukcheon watershed (303.3km2) data from 1998 to 1999. Generally, as the cell size of DEM increased, topographical changes were observed as the original range of elevation decreased. The processing time of watershed delineation and river network needed more time and effort on smaller cell size of DEM. The larger DEM demonstrated had some errors in the junction of river network which might effects on the simulation of water quantity and quality. The area weighted average watershed slope became lower but the length weighted average channel slope became higher as the DEM size increased. DEM resolution affected substantially on the topographical parameter but less on the hydrological simulation. Considering processing time and accuracy on hydrological simulation DEM mesh size of 100m is recommended for this watershed.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.299-302
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• 1999

Generation of a Digital Elevation Model (DEM) in remote sensing is an important application. The process of DEM generation often requires interpolation. This paper is aimed to introduce a class of interpolation algorithms using spectral information, which is widely used in geophysical applications, and to examine the applicability of the method to DEM interpolation. The interpolation process can be explained in two steps. The first step is for finding spectral information from the known data and the second step is finding missing data so as to follow the spectral trend found in the previous step. The interpolation algorithm has been tested for a real DEM data and problems in the DEM interpolation are discussed.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.7
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• pp.25-35
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• 2002

In this study, the effect of DEM (Digital Elevation Model) resolution (15m, 30m, 50m, 70m, 100m, 200m, 300m) on the hydrological simulation was examined using the BASINS (Better Assessment Science Integrating point and Nonpoint Source) for the Heukcheon watershed (303.3 ㎢) data from 1998 to 1999. Generally, as the cell size of DEM increased, topographical changes were observed as the original range of elevation decreased. The processing time of watershed delineation and river network needed more time and effort on smaller cell size of DEM. The larger DEM demonstrated had some errors in the junction of river network which might affect on the simulation of water quantity and quality. The area weighted average watershed slope became milder but the length weighted average channel slope became steeper as the DEM size increased. DEM resolution affected substantially on the topographical parameter but less on the hydrological simulation. Considering processing time and accuracy on hydrological simulation, DEM grid size of 100m is recommended for this range of watershed size.