• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.11-20
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• 2010

The purpose of this study is to analyze the images of the Military Academy, Naval Academy, Air Force Academy, Police Academy, and Armed Forces Nursing Academy using multidimensional scaling method. For this research, we surveyed 363 applicants to special purpose academies including Military Academies and Police College. The study showed that the Military, Naval, and Air Force Academies had stronger image than the Police Academy in the area of physical strength, tradition, and fellowship between senior and junior. On the other hand, the Police Academy had better image in the area of social activity and applicant's academic achievement. The Military Academy had been evaluated the best school among the three Academies in the area of applicant's academic achievement, educational environment, faculty, tradition, and fellowship between senior and junior.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.339-353
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• 2023

As the availability of high-resolution satellite imagery increases, improvement of positioning accuracy of satellite images is required. The importance of orthorectified images is also increasing, which removes relief displacement and establishes true localization of man-made structures. In this paper, we performed automated extraction of building rooftops and total building areas within original satellite images using the existing building height database. We relocated the rooftop sin their true position and generated an orthorectified building layer. The extracted total building areas were used to blank out building areas and generate true orthographic non-building layer. A final orthorectified image was provided by overlapping the building layer and non-building layer.We tested the proposed method with KOMPSAT-3 and KOMPSAT-3A satellite images and verified the results by overlapping with a digital topographical map. Test results showed that orthorectified building layers were generated with a position error of 0.4m.Through the proposed method, the feasibility of automated true orthoimage generation within dense urban areas was confirmed.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1015-1023
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• 2022

The Entry-Descent-Landing process of a lander involves many environmental and technical challenges. To solve these problems, recently, terrestrial relative navigation (TRN) technology has been essential for landers. TRN is a technology for estimating the position and attitude of a lander by comparing Inertial Measurement Unit (IMU) data and image data collected from a descending lander with pre-built reference data. In this paper, we present a method for generating descent dataset and extracting landmarks, which are key elements for developing TRN technologies to be used on Mars. The proposed method generates IMU data of a descending lander using a simulated Mars landing trajectory and generates descent images from high-resolution ortho-map and digital elevation map through a ray tracing technique. Landmark extraction is performed by an area-based extraction method due to the low-textured surfaces on Mars. In addition, search area reduction is carried out to improve matching accuracy and speed. The performance evaluation result for the descent dataset generation method showed that the proposed method can generate images that satisfy the imaging geometry. The performance evaluation result for the landmark extraction method showed that the proposed method ensures several meters of positioning accuracy while ensuring processing speed as fast as the feature-based methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.83-94
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• 2015

Recently, the necessity of spatial data in unaccessible area was challenged to set up various plans and policies for preparing the unification and the cooperative projects between South-North Korea. Therefore, this paper planned to evaluate the possibility of adopting the error tolerance in Geometric correction for 1/5,000 digital topographic mapping, using the PLEIADES images and the TerraSAR GCPs (Ground Control Points). The geometric correction was performed by changing the number and placement of GCPs by GPS (Global Positioning System) surveying, as the optimal placement of 5 GCPs were selected considering the geometric stability and steady rate. The positional accuracy evaluated by the TerraSAR GCPs, which were selected by optimal placement of GCPs. The RMSE in control points were X=±0.64m, Y=±0.46m, Z=±0.28m. While the result of geometric correction for PLEIADES images confirmed that the RMSE in control points were X=±0.34m, Y=±0.27m, Z=±0.11m, the RMSE in check points were X=±0.50m, Y=±0.30m, Z=±0.66m. Through this study, we believe if spatial data can integrate with the PLEIADES images and the optimal TerraSAR GCPs, it will be able to obtain the high-precision spatial data for adopting the regulation of 1/5,000 digital topographic map, which adjusts the computation as well as the error bound.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.401-410
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• 2020

In this study, a real-time Tactical UAS position compensation system based on image information developed to compensate for the weakness of location navigation information during GPS signal interference and jamming / spoofing attack is described. The Tactical UAS (KUS-FT) is capable of automatic flight by switching the mode from GPS/INS integrated navigation to DR/AHRS when GPS signal is lost. However, in the case of location navigation, errors accumulate over time due to dead reckoning (DR) using airspeed and azimuth which causes problems such as UAS positioning and data link antenna tracking. To minimize the accumulation of position error, based on the target data of specific region through image sensor, we developed a system that calculates the position using the UAS attitude, EO/IR (Electric Optic/Infra-Red) azimuth and elevation and numerical map data and corrects the calculated position in real-time. In addition, function and performance of the image information based real-time UAS position compensation system has been verified by ground test using GPS simulator and flight test in DR mode.

• Spatial Information Research
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• v.15 no.4
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• pp.363-370
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• 2007

This study has been carried for the development of the basic algorithm of helicopter navigation system based on TRN (Terrain Referenced Navigation) with information input from the GPS. The helicopter determines flight path due to Origination-Destination analysis on the Cartesian coordinate system of 3-D DTM. This system shows 3-D mesh map and the O-D flight path profile for the pilot's acknowledgement of the terrain, at first. The system builds TCF (terrain clearance floor) far the buffer zone upon the surface of ground relief to avid the ground collision. If the helicopter enters to the buffer zone during navigation, the real-time warning message which commands to raise the body pops up using Matlab menu. While departing or landing, control of the height of the body is possible. At present, the information (x, y, z coordinates) from the GPS is assumed to be input into the system every 92.8 m of horizontal distance while navigating along flight path. DTM of 3" interval has been adopted from that which was provided by ChumSungDae Co., Ltd..

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.348-353
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• 2008

Despite the increasing popularity of wireless sensor network, indoor positioning using low power IEEE 802.15.4 compliant radio had attracted an interest of many researchers in the last decade. Old fashionable indoor location sensing information has been presented in dull and unpleasant 2D image standard. This paper focused on visualizing high precision 3 dimensional RSSI-based (received signal strength indication) spatial sensing information in an interactive virtual reality on PDA. The developed system operates by capturing and extracting signal strength information at multiple pre-defined reference nodes to provide information in the area of interest, thus updating user's location in 3D indoor virtual map. VRML (Virtual Reality Modeling Language) which specifically developed for 3D objects modeling is utilized to design 3D indoor environment.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.39-48
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• 2015

Lately, Unmanned Aerial Vehicles(UAV), Unmanned Aerial Systems(UAS) or also often known as drones, as a data acquisition platform and as a measurement instrument are becoming attractive for many photogrammetric surveying applications, especially generation of the high density point clouds(HDPC). This paper presents the performance evaluation of a low-cost rotary wing quadrocopter UAS for generation of the HDPC in a test bed environment. Its performance was assessed by comparing the coordinates of UAS based HDPC to the results of Network RTK GNSS surveying with 62 ground check points. The results indicate that the position RMSE of the check points are ${\sigma}_H={\pm}0.102m$ in Horizonatal plane, and ${\sigma}_V={\pm}0.209m$ in vertical, and the maxium deviation of Elevation was 0.570m within block area of ortho-photo mosaic. Therefore the required level of accuracy at NGII for production of ortho-images mosaic at a scale of 1:1000 was reached, UAS based imagery was found to make use of it to update scale 1:1000 map. And also, since this results are less than or equal to the required level in working rule agreement for airborne laser scanning surveying of NGII for Digital Elevation Model generation of grids $1m{\times}1m$ and 1:1000 scale, could be applied with production of topographic map and ortho-image mosaic at a scale of 1:1000~1:2500 over small-scale areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.71-82
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• 2020

The existing transportation system, which is based on internal combustion engines, is rapidly being converted to electrification. Thus, eco-friendly public transportation with high transportation efficiency will continue to spread throughout the market in the near future. The purpose of this study is to compare and analyze the cognitive characteristics of passengers redgarding the technical and social factors of various public transportation means to help a successful introduction of eco-friendly public transit. Through a survey questionnaire (N=485), seven factors of seven transportation modes were evaluated and analyzed using principal component analysis. As a result, it is confirmed that potential passengers have high expectations for the eco-friendliness and city image of the eco-friendly buses. Also, it is confirmed that eco-friendly buses are superior in cleanliness and ride comfort than diesel buses. Given the study's results, this study identifies the cognitive characteristics of passengers regarding eco-friendly public transportation. We hope that these results will be used as basic information for image positioning and improved service with the use of eco-friendly transportation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.70-81
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• 2020

Point-by-point data, which is abundantly collected by vehicles with embedded GPS (Global Positioning System), generate useful information. These data facilitate decisions by transportation jurisdictions, and private vendors can monitor and investigate micro-scale driver behavior, traffic flow, and roadway movements. The information is applied to develop app-based route guidance and business models. Of these, speed data play a vital role in developing key parameters and applying agent-based information and services. Nevertheless, link speed values require different levels of physical storage and fidelity, depending on both collecting and reporting intervals. Given these circumstances, this study aimed to establish an appropriate collection interval to efficiently utilize Space Mean Speed information by vehicles with embedded GPS. We conducted a comparison of Probe-vehicle data and Image-based vehicle data to understand PE(Percentage Error). According to the study results, the PE of the Probe-vehicle data showed a 95% confidence level within an 8-second interval, which was chosen as the appropriate collection interval for Probe-vehicle data. It is our hope that the developed guidelines facilitate C-ITS, and autonomous driving service providers will use more reliable Space Mean Speed data to develop better related C-ITS and autonomous driving services.