• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.3-9
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• 2013

Various data like digital maps(1/1,000 or 1/5,000), field surveying, online materials and literatures are used for the preliminary investigation for urban development such as the feasibility evaluation, the profitability analysis, the zoning proposal, the zoning designation, and the land replotting planning. There are a couple of urban development methods like an expropriation, a replotting, a mixed-used method. The replotting method requires the consideration of land replotting types based on topography and building condition, which is not easy to gather data for the preliminary investigation maintaining the security of development planning. There are limitations of a preliminary investigation using aerial photos to detect topographic and building changes at specific period. GIS data combined with high-resolution imagery has advantages over the current dataset, which come from easy acquisition of various spatial resolution satellite images, wide swath coverage, the choice of imagery resolution satisfying a usage purpose, economic benefit comparing to aerial photos, and the calculation of distance and area on imagery from image modeling. For these reasons, the proposed method in this study enables to perform the more appropriate preliminary investigation using more accurate information.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.407-418
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• 2018

The frequency and risk of disasters are increasing due to environmental and social factors. In order to respond effectively to disasters that occur unexpectedly, it is very important to quickly obtain up-to-date information about target area. It is possible to intuitively judge the situation about the area through the image-map generated at high speed, so that it can cope with disaster quickly and effectively. In this study, we propose an image-map generation and visualization system from UAV images for real-time disaster monitoring. The proposed system consists of aerial segment and ground segment. In the aerial segment, the UAV system acquires the sensory data from digital camera and GPS/IMU sensor. Communication module transmits it to the ground server in real time. In the ground segment, the transmitted sensor data are processed to generate image-maps and the image-maps are visualized on the geo-portal. We conducted experiment to check the accuracy of the image-map using the system. Check points were obtained through ground survey in the data acquisition area. When calculating the difference between adjacent image maps, the relative accuracy was 1.58 m. We confirmed the absolute accuracy of the image map for the position measured from the individual image map. It is confirmed that the map is matched to the existing map with an absolute accuracy of 0.75 m. We confirmed the processing time of each step until the visualization of the image-map. When the image-map was generated with GSD 10 cm, it took 1.67 seconds to visualize. It is expected that the proposed system can be applied to real - time monitoring for disaster response.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1251-1260
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• 2018

High-quality sea-ice surface models generated from aerial images can be used effectively as field data for developing satellite-based remote sensing methods but also as analysis data for understanding geometric variations of Arctic sea-ice. However, the lack of texture information on sea-ice surfaces can reduce the accuracy of image matching. In this paper, we analyze the performance of matching cost functions for homogeneous sea-ice surfaces as a part of high-quality sea-ice surface model generation. The matching cost functions include sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC) in image domain and phase correlation (PC), orientation correlation (OC), and gradient correlation (GC) in frequency domain. In order to analyze the matching performance for texture changes clearly and objectively, a new evaluation methodology based on the principle of object-space matching technique was introduced. Experimental results showed that it is possible to secure reliability and accuracy of image matching only when optimal search windows are variably applied to each matching point in textureless regions such as sea-ice surfaces. Among the matching cost functions, NCC and ZNCC showed the best performance for texture changes.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.101-110
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• 2010

The increased occurrence of flooding due to typhoons and local rainfall has necessitated damage prevention through the systematic construction of damage history and quantitative analysis of flood prediction data. In this study, we constructed a disaster information map for practical use by combining digital images and continuous cadastral maps of damaged areas using a geographic information system to provide basic data and attribute information. In addition, we predicted the areas at risk of flash floods by calculating the flood capacity of the study area for different rainfall frequencies through flood inundation simulation, which was used to obtain comprehensive disaster information. Further, we calculated the extent of the flooded area and the damage rate for different rainfall frequencies using cadastral information. Flood inundation simulation in the case of heavy rainfall was found to help improve the ability to react to a flood and enhance the efficiency of rescue work by supporting decision-making for disaster management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.487-493
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• 2014

A geographic survey, which requires much of working hours in the digital mapping process, is consisted with the complementary survey and the attribute survey of topography and topographic features, and depended on the field survey. In previous research, using the location-based image had been recommended for diminishing the workload of field survey and post processing. For this research, we have developed the hardware and software for gathering and processing the location-based images with referencing results from the previous research. Those Geographic surveys were performed using developed system on 1/5,000 map sheets for Si and Gun area, respectively. The results have been evaluated as the mobile geographic survey system were able to replace the large part of field survey, and also the working hours were decreased by 37.5% at Si area. However, the complementary survey was needed for the attributes of topography and topographic features that were occluded by the parked vehicles or located in the areas without entry of vehicles.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.411-419
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• 2013

Research on developing algorithms for building modeling such as extracting outlines of the buildings and segmenting patches of the roofs using aerial images or LiDAR data are active. However, utilizing information from the building model is not well implemented yet. This study aims to propose a scheme for search identical or similar shape of buildings by utilizing graph topology pattern matching under the assumptions: (1) Buildings were modeled beforehand using imagery or LiDAR data, or (2) 3D building data from digital maps are available. Side walls, segmented roofs and footprints were represented as nodes, and relationships among the nodes were defined using graph topology. Topology graph database was generated and pattern matching was performed with buildings of various shapes. The results show that efficiency of the proposed method in terms of reliability of matching and database structure. In addition, flexibility in the search was achieved by altering conditions for the pattern matching. Furthermore, topology graph representation could be used as scale and rotation invariant shape descriptor.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.2 s.4
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• pp.67-79
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• 1994

Recently, the rapid economic growth has caused urban problems due to the increase of urban population and the rapid expansion as a result of exodus phenomenon in rural territories. In order to solve the problems, we need to perform rational and effective plans for national land development. Generally, we need speedy and accurate topographical information of the object area to go ahead with balanced national land development. Acquisition method for topographical data include utilization of existing geographic information such as national base maps and related thematic maps and grasping of accurate present condition of object area using aerial photographies or satellite images. When the object area is small, existing methods for acquiring topographical information reveals imitations in accuracy, speed and economic aspect. Therefore, development of a new method is in order. As a result of this study, we recogized that Photo Balloon System to be manufactured and digital ortho-map to be generated could be used to obtain a topographical information for small areas.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.488-490
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• 2009

The Spatial Image contents of Geomorphology 3-D environment is focused by the requirement and importance in the fields such as, national land development plan, telecommunication facility management, railway construction, general construction engineering, Ubiquitous city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. This As the results, We confirmed the solutions of varieties application for railway facilities management using 3-D spatial image contents and database design. Also, I suggested that U-city using topographical modeling about matching methods of high density elevation value using 3-D aerial photo with laser data are best approach for detail stereo modeling and simulation. There for of this, Using of rapid spatial information generation by various images and laser data through matching methods for the make of Spatial data base management inplementation are very powerful and much application of our life and real worlds.

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.340-350
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• 2014

Recently, TMDL has been implemented to estimate the amount of pollutant loads and to establish proper mitigation strategy to decrease the pollutant loads by the Ministry of Environment. To estimate the amount of pollutant loads with reasonable accuracy, securing landcover map with periodically updating is essential. However, in reality, due to the technical and financial difficulties, the landcover map has not been updated annually. Hence, this study mainly aims to suggest an effective GIS-based updating method in order to promote utilization of landcover map in the estimation of pollutant loads. Bupyeong-gu at the City of Incheon with the total area of $31.98km^2$ was chosen for this study and spatial data including digital topographic maps, ortho aerial photo, and satellite images were collected and utilized. A total of 7,235 feature entities were newly produced through the updating process of five steps and it was revealed that the classification of landcover with the total area of $3.34km^2$ was to be changed. The validity and feasibility of the suggested method were proved with the accuracy of 97.9% from the field verification. Further study needs to be made for devising more automated method to update landcover map to facilitate TMDL for individual local governments.