• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.621-626
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Extraction of 3D building information from high resolution satellite imagery is one of the most active research topics. There have been many previous works to extract 3D information based on stereo analysis, including sensor modelling. Practically, it is not easy to obtain stereo high resolution satellite images. On single image performance, most studies applied the roof-bottom points or shadow length extracted manually to sensor models with DEM. It is not suitable to apply these algorithms for dense buildings. We aim to extract 3D building information from a single satellite image in a simple and practical way. To measure as many buildings as possible, in this paper, we suggested a new way to extract building height by triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and decrease the digitizing error and the computation efficiency.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.141-152
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• 2008

The 3D building modeling is one of crucial components in constructing 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes, which indeed take great amount of time and efforts. In recent years, many researches on 3D building modeling using aerial LiDAR data have been actively performed to aim at overcoming the limitations of existing 3D building modeling methods. Either techniques with interpolated grid data or data fusion with digital map and images have been investigated in most of existing researches on 3D building modeling with aerial LiDAR data. The paper proposed a method of 3D building modeling with LiDAR data only. Firstly, octree-based segmentation is applied recursively to LiDAR data classified as buildings in 3D space until there are no more LiDAR points to be segmented. Once octree-based segmentation is completed, each segmented patch is thereafter merged together based on its geometric spatial characteristics. Secondly, building model components are created with merged patches. Finally, a 3D building model is generated and composed with building model components. The experimental results with real LiDAR data showed that the proposed method was capable of modeling various types of 3D buildings.

• Spatial Information Research
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• v.23 no.1
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• pp.49-57
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• 2015

Due to high density of population and progress of high building construction technologies, the number of high buildings has been increasing. Several information services have been provided to figure out complex indoor structures of building such as indoor navigations and indoor map services. The most fundamental information for these services are indoor network information. Indoor network in building provides topological connectivity between spaces unlike geometric information of buildings. In order to make indoor network information, we have to edit network manually or derive network properties based on the geometric data of buildings. This process is not easy for complex buildings. In this paper, we suggest a method to generate indoor network automatically based on crowdsourcing. From the collected individual trajectories, we derive indoor network information with crowdsourcing. We validate our method with a sample set of trajectory data and the result shows that our method is practical if the indoor positioning technology is reasonably accurate.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.43-53
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• 2006

As NGIS project has been implemented in 1995 and effectiveness of geospatial information increased, Digital maps serve several purpose in administrative, living, and the variety of industrial fields. But, Digital maps have difficulties in application of managing urban facilities due to many differences with real world information caused by high update cost and long generation period. This paper suggests an update method of building layers of digital map in urban area; first, we verify the filtered building information using digital areal imagery and LiDAR data which is high-accurate and also can be faster and more economical in 3D information acquisition, and finally update building layers by comparing with the existed digital map. Future research will concentrate on automatic removal of the small and the tree regions, discrimination of buildings and vegetation for generating and updating building layers using LiDAR data.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.321-326
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• 2002

상가건물임대차보호법의 시행령을 제정하는데 필요한 근거정보를 수집하기 위한 임차 사업체조사의 표본설계과정과 추정법을 설명하고 주요 조사결과를 제시하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.4
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• pp.335-341
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• 2006

This paper aims at developing an efficient method that extracts building using local spatial association of raw LiDAR data without setting up empirical variables such as a minimum building area, and applying the method to survey data to evaluate the efficiency of that. To do this, LISA(Local Indicatiors of Spatial Association) statistics are used which reflect local variations that can be appeared in the research area. It can be also a preprocess that detects spatial outliers through the significance test of LISA statistics and interpolate using kernel estimation. Boundaries of buildings as well as buildings can be extracted based on quadrant of Moran Scatterplot. Experimental results show that the proposed method is promising in extracting buildings from LiDAR data automatically.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.413-420
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• 2011

This study is to extract landmark buildings for pedestrian navigation from the existing spatial data sets automatically. At first, we defined candidates for landmark based on sight of pedestrian, then extracted final landmark by evaluating attributes of each candidate. The attribute is evaluated with relative or absolute criteria depending on the nature of each attribute. Landmarks extracted through the proposed method are compared to existing landmarks for vehicle and assessment of the validity and the applicability is performed. As a result, extracted Landmarks are expected to help guiding pedestrian effectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.3
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• pp.313-322
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• 2005

Rapid advances in technology and changes in human and cultural activities bring about changes to the earth surface in terms of spatial extension as well as time frame of the changes. Such advances introduce shorter updating frequency of maps and geospatial database. To satisfy these requirements, recent research efforts in the geoinformatics field have been focused on the automation and speeding up of the mapping processes which resulted in products such as the digital photogrammetric workstation, GPSIINS, applications of satellite imagery, automatic feature extraction and the LiDAR system. The possibility of automatically extracting buildings and generating contours from airborne LiDAR data has received much attention because LiDAR data produce promising results. However, compared with the manually derived building footprints using traditional photogrammetric process, more investigation and analysis need to be carried out in terms of accuracy and efficiency. On the other hand, generation of the contours with LiDAR data is more efficient and economical in terms of the quality and accuracy. In this study, the effects of various conditions of the pre-processing phase and the subsequent building extraction and contour generation phases for digital mapping have on the accuracy were investigated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.203-215
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• 2017

Recently, interest in Pedestrian Navigation Service (PNS) is being increased due to the diffusion of smart phone and the improvement of location determination technology and it is efficient to use landmarks in route guidance for pedestrians due to the characteristics of pedestrians' movement and success rate of path finding. Accordingly, researches on extracting landmarks have been progressed. However, preceding researches have a limit that they only considered the difference between buildings and did not consider visual attention of maps in display of PNS. This study improves this problem by defining building attributes as local variable and global variable. Local variables reflect the saliency of buildings by representing the difference between buildings and global variables reflects the visual attention by representing the inherent characteristics of buildings. Also, this study considers the connectivity of network and solves the overlapping problem of landmark candidate groups by network voronoi diagram. To extract landmarks, we defined building attribute data based on preceding researches. Next, we selected a choice point for pedestrians in pedestrian network data, and determined landmark candidate groups at each choice point. Building attribute data were calculated in the extracted landmark candidate groups and finally landmarks were extracted by principal component analysis. We applied the proposed method to a part of Gwanak-gu, Seoul and this study evaluated the extracted landmarks by making a comparison with labels and landmarks used by portal sites such as the NAVER and the DAUM. In conclusion, 132 landmarks (60.3%) among 219 landmarks of the NAVER and the DAUM were extracted by the proposed method and we confirmed that 228 landmarks which there are not labels or landmarks in the NAVER and the DAUM were helpful to determine a change of direction in path finding of local level.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.11-15
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• 1999