• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.55-61
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• 2010

Using 3D point data implemented from terrestrial LiDAR, this research has modelled geospatial data in 2 categories(gridded & un-gridded) and conducted LOS analysis experiment using outcome from the modeling exercise. To compare LOS analysis results from each of the 2 models in the above, maximum LOS (line of sight) range in the experimental area was specified as 30m in Area A, 40m in Area B and 50m in Area C and the time taken by LOS analysis and the number of visible points were measured. As for the LOS analysis experiment results, in comparison with the gridded model, the un-gridded model took about 3.9 times more time in Area A, 5.4 times in Area B and 6.5 times in Area C. In addition, about 0.97 times fewer points were measured in Area A, 0.93 times in Area B and 0.94 times in Area C. The difference between gridded model and un-gridded model in terms of the time taken by LOS analysis increased, as the maximum LOS range extended. On the other hand, the number visible points did not vary significantly in reference to the size of visible range.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.195-202
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• 2006

The infiltration route analysis is a military application using geospatial information technology. The result of the analysis would present vulnerable routes for potential enemy infiltration. In order to find the susceptible routes, optimal path search algorithms (Dijkstra's and $A^*$) were used to minimize the cost function, summation of detection probability. The cost function was produced by capability of TOD (Thermal Observation Device), results of viewshed analysis using DEM (Digital Elevation Model) and two related geospatial information coverages (obstacle and vegetation) extracted from VITD (Vector product Interim Terrain Data). With respect to 50m by 50m cells, the individual cost was computed and recorded, and then the optimal infiltration routes was found while minimizing summation of the costs on the routes. The proposed algorithm was experimented in Daejeon region in South Korea. The test results show that Dijkstra's and $A^*$ algorithms do not present significant differences, but A* algorithm shows a better efficiency. This application can be used for both infiltration and surveillance. Using simulation of moving TOD, the most vulnerable routes can be detected for infiltration purpose. On the other hands, it can be inversely used for selection of the best locations of TOD. This is an example of powerful geospatial solution for military application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.281-284
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• 2002

Geographic Information System (GIS) has advantage of analyzing spatial distributed data and handling spatial data for hydrologic analysis. Hydrologic Engineering Center's Hydrologic Modeling System(HEC-HMS) with HEC-GeoHMS was used to analyze flood runoff at agricultural small watershed. HEC-GeoHMS, which is an ArcView GIS extension designed to process geospatial data for HEC-HMS, is a useful tool for storing, managing, analyzing, and displaying spatially distributed data. Hydroligical component including peak discharge, time to peak, direct runoff, baseflow for Balhan study watershed, which is located in Whasung city, Kyunggi province, having an area of $29.79km^2$, were calculated using the HEC-HMS model with HEC-GeoHMS.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.23-29
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• 1996

The purpose of this study is to develope an Object-Oriented Graphic database management system to handle geographic data of geographic information systems. As the result of this study, unstructured vector model was developed to handle geographic data and graphic database management was implemented by object-oriented programming. This study was focused on liking function between graphic data and attribute data, and not focused on network analysis function.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.23-31
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• 2007

The objective of the study is to prepare input data for FIA (Flood Inundation Analysis) & FDA (Flood Damage Assessment) through rainfall-runoff simulation by HEC-HMS model. For HwaOng watershed (235.6 $km^{2}$), HEC-HMS was calibrated using 6 storm events. Geospatial data processors, HEC-GeoHMS is used for HEC-HMS basin input data. The parameters of rainfall loss rate and unit hydrograph are optimized from the observed data. HEC-HMS was applied to simulate rainfall-runoff relation to frequency storm at the HwaOng watershed. The results will be used for mitigating and predicting the flood damage after river routing and inundation propagation analysis through various flood scenarios.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.79-88
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• 2015

In any production and construction of geospatial information covering surveying, survey control point is a vital geospatial information. Survey control points in South Korea are currently classified as following: national control points, public control points, and cadastral control points. Each of these different categories of survey control points act as a basis and sets perimeters for the production, management and operation of subjects within the category. Universal standard, the unified format between different survey control points, also, are not yet defined, causing difference in basic information provided by altering categories and disturbance in connecting, managing, utilizing and operating survey control points. Establishment of a standard regarding survey control points, is therefore required for the efficacy of their utilization. This study, to solve such inadequacies, selects management items for creation of standardized survey control point, by investigating domestically and internationally the status of operating survey control points, determining data model for management, establishing TTA and agency standards, and establishing of activation methodology for survey control point standards.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.67-73
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• 2016

The present study evaluated the blocking effect of natural and artificial topography on sunshine duration in the southern coastal area of Haui-do. The geospatial data for the target area was constructed by geographic information system(GIS) data. Three-dimensional modeling based on solar azimuth and altitude angles was conducted for the assessment of sunshine environment. The sunshine area was evaluated over 80~90% of the target area in the daytime, especially in summer. The blocking effect of mountainous terrain on sunshine duration was presented at the northern residential area in the late afternoon. There was also the effect of artificial topography by construction of fill-up bank on sunshine environment at the southern residential area early in the morning and the south-western part of salt field in the late afternoon.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.396-407
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• 2015

The literature about intelligence assets allocation focused on mainly single or partial assets such as TOD and GSR. Thus, it is limited in application to the actual environment of operating various assets. In addition, field units have generally vulnerabilities because of depending on qualitative analysis. Therefore, we need a methodology to ensure the validity and reliability of intelligence asset allocation. In this study, detection probability was generated using digital geospatial data in MGIS (Military Geographic Information System) and simulation logic of BCTP (Battle Commander Training Programs) in the R.O.K army. Then, the optimal allocation mathematical model applied concept of simultaneous integrated management, which was developed based on the partial set covering model. Also, the proposed GA (Genetic Algorithm) provided superior results compared to the mathematical model. Consequently, this study will support effectively decision making by the commander by offering the best alternatives for optimal allocation within a reasonable time.