• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.60-67
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• 2024

The majority of civil aviation accidents are caused by human factors, and especially for rotary-wing aircraft, accidents often occur in situations where pilots unexpectedly or unintentionally enter into instrument meteorological conditions (IIMC). This research analyzed the error rates of rotary-wing aircraft pilots under low visibility conditions from various angles to gain insights into flight characteristics and to explore measures to reduce accidents in IIMC situations. The occurrence rate of errors by pilots under low visibility conditions was examined using a flight simulator equipped with motion, with 65 pilots participating in the experiment. Flight data obtained through the experiment were used to aggregate and analyze the number of errors under various conditions, such as reductions in flight visibility, the presence or absence of spatial disorientation, and the pilot's qualifications. The analysis revealed peculiarities in flight characteristics under various conditions, and significant differences were found in the rate of error occurrence according to the pilot's qualification level, possession of instrument flight rules (IFR) qualifications, and during different phases of flight. The results of this research are expected to contribute significantly to the prevention of aircraft accidents in IIMC situations by improving pilot education and training programs.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.1-8
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• 2024

We present a novel algorithm for creating 2D maps tailored for autonomous navigation within orchards. Recognizing that fruit trees in orchards are typically aligned in rows, our primary goal is to accurately detect these tree rows and project this information onto the map. Initially, we propose a simple algorithm that recognizes trees from point cloud data by analyzing the spatial distribution of points. We then introduce a method for detecting fruit tree rows based on the positions of recognized fruit trees, which are integrated into the 2D orchard map. Validation of the proposed approach was conducted using real-world orchard point cloud data acquired via LiDAR. The results demonstrate high tree detection accuracy of 90% and precise tree row mapping, confirming the method's efficacy. Additionally, the generated maps facilitate the development of natural navigation paths that align with the orchard's layout.

• Journal of Navigation and Port Research
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• v.48 no.4
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• pp.310-320
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• 2024

This study aims to develop evacuation facilities for use during disasters such as fires and floods at an Underwater Research Station, which houses several researchers for extended periods. Initially, the residential space characteristics and the disaster and evacuation features of the Underwater Research Station are identified through a case study of similar underwater facilities. Subsequently, evacuation scenarios in the event of a disaster are formulated based on the spatial layout of the Underwater Research Station, and the requisite evacuation facilities are determined in accordance with the evacuation routes. Furthermore, by reviewing the standards for evacuation facilities of buildings, submarines, and underwater habitats, we establish suitable standards for the evacuation facilities of the Underwater Research Station and apply these standards in planning the evacuation facilities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.223-233
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• 2018

In this study was classified the cadastral control points and parcel boundary points into 40m, 100m by flight altitude of UAV (Unmanned Aerial Vehicle) which compared the coordinates extracted from the orthophoto with the parcel boundary point coordinates by GNSS (Global Navigation Satellite System) ground survey. As a results of this study, first, in the spatial resolution analysis that the average error of the orthoimage by flight altitude were 0.024m at 40m, and 0.034m at 100m which were higher 40m than 100m for spatial resolution of orthophotos and position accuracy. Second, in order to analyze the accuracy of image recognition by airmark of flight altitude that was divided into three cases of nothing, green, and red of RMSE (Root Mean Square Error) were X=0.039m, Y=0.019m and Z=0.055m, the highest accuracy. Third, the result of the comparison between orthophotos and field survey results that showed the total RMSE error of the cadastral control points were X=0.029m, Y=0.028m, H=0.051m, and the parcel boundary points were X=0.041m, Y=0.030m. In conclusion, based on the results of this study, it is expected that if the average error of flight altitude is limited to less than 0.05m in the legal regulations related to orthophotos for cadastral surveying, it will be an economical and efficient method for cadastral survey as well as spatial information acquisition.

• Spatial Information Research
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• v.20 no.4
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• pp.29-36
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• 2012

The low-carbon freight transportation system was introduced due to increase traffic congestion cost and carbon-dioxide for global climate change according to expanding city logistics demands. It is necessary to create 3D-based road network map for representing realistic road geometry with consideration of fuel consumption and carbon emissions. This study propose that 3D road network model expressed to realistic topography and road structure within trunk road for intercity freight through overlaying 2D-based transport-related thematic map and 1m-resolution DEM. The 3D-based road network map for the experimental road sections(Pyeongtaek harbor-Uiwang IC) was verified by GPS/INS survey and fuel consumption simulation. The results corresponded to effectively reflect realistic road geometry (RMSE=0.87m) except some complex structure such as overpass, and also actual fuel consumption. We expect that Green-based freight route planning and navigation system reflected on 3D geometry of complex road structure will be developed for effectively resolving energy and environmental problems.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.195-199
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• 2009

Augmented reality is a field of computer research which deals with the combination of real-world and computer-generated data, where computer graphics objects are blended into real footage in real time and it has tremendous potential in visualizing geospatial information. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or marker based approaches. Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed RF based tracking and localization. However, it does cause deployment problems of large sensors and readers. In this paper, we present a noble markerless AR approach for indoor navigation system only using a camera. We will apply this work to mobile seamless indoor/outdoor u-GIS system.

• Spatial Information Research
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• v.17 no.1
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• pp.1-14
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• 2009

Demands for a system which enable users to retrieve any kind of geographic and regional information over the Web have been increasing. However, in order to obtain geographic or regional information over the web, users still need to search web pages related to region by inputting keywords and to arrange the searched results with map. We can solve that problem by using the fact that most of geographic and regional information contain geographic keywords related to location. In this paper, we propose a system to retrieve geographic and regional information efficiently. For the purpose, we present a conceptual model based on three layers of "Real-World", "Knowledge", and "Applications", from the web space and construct the above link process. These layers are connected to each other and enable users to navigation information over the linkage. Especially, users can obtain various correlated information about geographic information and properties.

• Spatial Information Research
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• v.16 no.4
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• pp.455-465
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• 2008

Augmented reality (AR) has tremendous potential in visualizing geospatial information, especially on the actual physical scenes. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or ubiquitous marker based approaches. Although there are several papers written with vision based markerless tracking, previous approaches provide fairly good results only in largely under "controlled environments." Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed Radio Frequency (RF) based tracking and localization. However, it does cause deployment problems of large RF-based sensors and readers. In this paper, we present a noble markerless AR approach for indoor (possible outdoor, too) navigation system only using monoSLAM (Monocular Simultaneous Localization and Map building) algorithm to full-fill our grand effort to develop mobile seamless indoor/outdoor u-GIS system. The paper briefly explains the basic SLAM algorithm, then the implementation of our system.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.59-67
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• 2005

Building information is primary source in many applications such as mapping, telecommunication, car navigation and virtual city modeling. While aerial CCD images which are captured by passive sensor(digital camera) provide horizontal positioning in high accuracy, it is far difficult to process them in automatic fashion due to their inherent properties such as perspective projection and occlusion. On the other hand, LIDAR system offers 3D information about each surface rapidly and accurately in the form of irregularly distributed point clouds. Contrary to the optical images, it is much difficult to obtain semantic information such as building boundary and object segmentation. Photogrammetry and LIDAR have their own major advantages and drawbacks for reconstructing earth surfaces. The purpose of this investigation is to automatically obtain spatial information of 3D buildings by fusing LIDAR data with aerial CCD image. The experimental results show that most of the complex buildings are efficiently extracted by the proposed method and signalize that fusing LIDAR data and aerial CCD image improves feasibility of the automatic detection and extraction of buildings in automatic fashion.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.4 s.22
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• pp.69-76
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• 2002

Nowadays information is very important for Civil Engineering. This information is acquiredmostly via Surveying & Geo-spatial Information System. Also this information is close to the ITS(Intelligent Transformation System), Navigation, Facility Management, and Digital Mapping, etc and applicable to versatile fields from now on. And in surveying fields, GPS satellites are introduced newly and play a great rules. In this study, RTK(Real-Time Kinematic GPS), one of the positioning technology with GPS satellites, is used for the production of Plane Figure of Campus. The results shows that it is possible to extract the information for some part of a flowerbed and road, but not so for the buildings surrounded. Therefore this give occasion to the a lowering of work effectiveness over the total work-flow. So at such a time, it will be expected that the supplementary systems such TS(Total Station), Plane-table, and theodolite, etc have to be used.