• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.265-271
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• 2010

This paper discusses a new software package, DEM_Comp, developed for effectively compressing large digital elevation model (DEM) data sets based on Lempel-Ziv-Welch (LZW) compression and Huffman coding. DEM_Comp was developed using the $C^{++}$ language running on a Windows-series operating system. DEM_Comp was also tested on various test sites with different territorial attributes, and the results were evaluated. Recently, a high-resolution version of the DEM has been obtained using new equipment and the related technologies of LiDAR (LIght Detection And Radar) and SAR (Synthetic Aperture Radar). DEM compression is useful because it helps reduce the disk space or transmission bandwidth. Generally, data compression is divided into two processes: i) analyzing the relationships in the data and ii) deciding on the compression and storage methods. DEM_Comp was developed using a three-step compression algorithm applying a DEM with a regular grid, Lempel-Ziv compression, and Huffman coding. When pre-processing alone was used on high- and low-relief terrain, the efficiency was approximately 83%, but after completing all three steps of the algorithm, this increased to 97%. Compared with general commercial compression software, these results show approximately 14% better performance. DEM_Comp as developed in this research features a more efficient way of distributing, storing, and managing large high-resolution DEMs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.431-439
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• 2010

Cross-interferometic synthetic aperture radar (CInSAR) technique from ERS-2 and Envisat images is capable of generating submeter-accuracy digital elevation model (DEM). However, it is very difficult to produce high-quality CInSAR-derived DEM due to the difference in the azimuth and range pixel size between ERS-2 and Envisat images as well as the small height ambiguity of CInSAR interferogram. In this study, we have proposed an efficient method to overcome the problems, produced a high-quality DEM over northern Alaska, and compared the CInSAR-derived DEM with the national elevation dataset (NED) DEM from U.S. Geological Survey. In the proposed method, azimuth common band filtering is applied in the radar raw data processing to mitigate the mis-registation due to the difference in the azimuth and range pixel size, and differential SAR interferogram (DInSAR) is used for reducing the unwrapping error occurred by the high fringe rate of CInSAR interferogram. Using the CInSAR DEM, we have identified and corrected man-made artifacts in the NED DEM. The wave number analysis further confirms that the CInSAR DEM has valid Signal in the high frequency of more than 0.08 radians/m (about 40m) while the NED DEM does not. Our results indicate that the CInSAR DEM is superior to the NED DEM in terms of both height precision and ground resolution.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.34-43
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• 2018

DEM(Digital Elevation Model) being fundamental data in geospatial domain is produced from different data and using various methods. As they are derived their precision varies and altering derivative in application. In this work, we compare two widely used DEMs namely(Advanced Land Observing Satellite World 3D 30m and Shuttle Radar Topography Mission Global 30m) around coastal islands in Gyeongsangnam-do, South Korea. First statistics of each DEM were calculated and later overlapped in Landsat image for visual comparison of areas below and above zero-meter elevation. As a result, it was found that DEMs were highly correlated with each other and had similar statistics. Besides having few high differences in hilly land area, they were able to represent the coastal lines. It has also been noted that they have many negative values and should carefully select study area covering full watershed in coastal regions to avoid negative elevation even after filling the sinks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1213-1221
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• 2022

In Electronic Warfare, the need to develop a jamming system that protects our location information from enemy radar is constantly increasing. The jamming system normally uses wide-band DRFM(Digital Radio Frequency Memory) that processes the entire bandwidth at once. However, it is difficult to jam if there is a CW(Continuous Wave) interference signal in the band. Recently, instead of wide-band signal processing, a structure using a filter bank that divides the entire band into several sub-bands and processes each sub-band independently has been proposed. Although it is possible to handle interference signal through the filter bank structure, spurious signal occurs when the signal is received at a boundary frequency between sub-bands. Spurious signal makes a output power of jamming signal distributed, resulting in lower JSR(Jamming to Signal Ratio) and less jamming effect. This paper proposes an over-sampled channelized DRFM structure that enables interference response and prevents spurious signal for sub-band boundary frequency input.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.13-19
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• 2014

To develop a wind farm in a mountainous terrain like Korea, it is generally more advantageous to install wind turbines along a mountain ridge where has relatively better wind resource because that is open in all directions and free from shielding by the surrounding topography. In this study, the SRTM (Shuttle Radar Topography Mission) v4.1 3 arc-second resolution digital elevation database and the geomorphometric characterization software LandSerf v2.3 are used to extract ridge lines for assessing a wind farm siting in mountainous terrain. The effectiveness of wind farm siting along a ridge line is confirmed that the most of wind turbines in the Gangwon, Taegisan, and Maebongsan wind farms in Korea's mountainous terrain are placed along the primary and secondary ridge lines where wind resource is relatively outstanding.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.158-164
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• 1999

This paper investigated and evaluated the NASA's Shuttle Imaging Radar-C (SIR-C) multiple frequency SAR data for differential backscattering effects of microwave from the surface geological materials overlying the skarn type mineralization. Although an integrated approach in mineral exploration is more cost effective and is well in use, there are still many technical and scientific issues to be further investigated and researched. In this study we have reprocessed several sets of previously surveyed exploration data and experimented with fuzzy logic digital fusion of the preprocessed data with respect to chosen exploration targets. Among the numerous fuzzy logic operators, which are currently available for a data driven integrated exploration strategy, we used varying combinations of fuzzy MIN, fuzzy MAX, and fuzzy SUM operators along with Gamma operator for fusion of exploration data, including the contact metamorphic zone information. The final exploration target tested was a skarn type W-Mo-F mineralization in the study area. The fuzzy logic derived mineral potential anomaly almost exactly matched the differential backscattering anomalies on the C-band and L-band SIR_C data when overlaid on each other. Although this high degree of correlation between these two data sets is remarkable, the differential backscattering anomaly over the skarn type W-Mo-F mineralization in the study area requires further investigation.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.203-209
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• 2016

Among the various fields in the communications, navigation, and surveillance/air traffic management (CNS/ATM) scheme, the surveillance field, which includes an automatic dependent surveillance - broadcast (ADS-B) system and a multilateration (MLAT) system, is implemented using satellite and digital communications technology. These systems provide better performance than radar, but still incur position error. To reduce the error, we propose an efficient information fusion method called the reweighted convex combination method for ADS-B and MLAT systems. The reweighted convex combination method improves aircraft tracking performance compared to the original convex combination method by readjusting the weights given to these systems. In this paper, we prove that the reweighted convex combination method always provides better performance than the original convex combination method. Performance from the fusion of ADS-B and MLAT improves an average of 51.51% when compared to the original data.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.69-77
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• 2017

S The need for an automated geo-positioning approach for near real-time results and to boost cost-effectiveness has become increasingly urgent. Following this trend, a new approach to automatically compensate for the bias of the rational function model (RFM) was proposed. The core idea of this approach is to remove the bias of RFM only using tie points, which are corrected by matching with the digital elevation model (DEM) without any additional ground control points (GCPs). However, there has to be a additional evaluation according to the quality of DEM because DEM is used as a core element in this approach. To address this issue, this paper compared the quality effects of DEM in the conduct of the this approach using the Shuttle Radar Topographic Mission (SRTM) DEM with the spatial resolution of 90m. and the National Geographic Information Institute (NGII) DEM with the spatial resolution of 5m. One KOMPSAT-2 stereo-pair image acquired at Busan, Korea was used as experimental data. The accuracy was compared to 29 check points acquired by GPS surveying. After bias-compensation using the two DEMs, the Root Mean Square (RMS) errors were less than 6 m in all coordinate components. When SRTM DEM was used, the RMSE vector was about 11.2m. On the other hand, when NGII DEM was used, the RMSE vector was about 7.8 m. The experimental results showed that automated geo-positioning approach can be accomplished more effectively by using NGII DEM with higher resolution than SRTM DEM.

• 한국공간정보시스템학회:학술대회논문집
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• 2000.06a
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• pp.67-76
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• 2000

Recently, SAR Interferometry method is actively being studied as a new technic in topographic mapping using satellite imageries. it extract height values using two SAR imageries covering same areas. Unlike when using SPOT imageries, it isn't affected by atmospheric conditions and time. But it is difficult to process radar imageries and the height accuracy is very low where relief displacements are high. In this study, we produced DEM(Digital Elevation Model) using ERS-1, ERS-2 tandem data and analysed the height accuracy over 14 ground control points. The mean error in height was 14.06m. But when using airborne SAR data, it Is expected that we can produce more accurate DEM which will be able to ue used in updating 1/10,000 or 1/25,000 map.