• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.697-702
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• 2015

Recently, the need of effective technologies for disaster damage investigation is increasing. Development of geospatial information technology like UAV is the useful method for quick damage investigation. In this research, to assess the applicability of geospatial information constructed by UAV, we produced ortho images about research area and compared them with digital topographic maps for accuracy evaluation. As a result, ortho images showed within 30cm difference with 1/5,000 digital topographic maps, we could present the possibility to utilize for producing disaster information using UAV because of its effective construction and calculation of disaster information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.49-56
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• 2020

In this study, we analyzed the sharpness of UAV-images using the gradient formula and produced a MATLAB GUI (Graphical User Interface)-based sharpness analysis tool for easy use. In order to verify the reliability of the proposed sharpness analysis method, sharpness values of the UAV-images measured by the proposed method were compared with those by measured the commercial software Metashape of the Agisoft. As a result of measuring the sharpness with both tools on 10 UAV-images, sharpness values themselves were different from each other for the same image. However, there was constant bias of 011 ~ 0.20 between two results, and then the same sharpness was obtained by eliminating this bias. This fact proved the reliability of the proposed sharpness analysis method in this study. In addition, in order to verify the practicality of the proposed sharpness analysis method, unsharp images were classified as low quality ones, and the quality of orthoimages was compared each other, which were generated included low quality images and excluded them. As a result, the quality of orthoimage including low quality images could not be analyzed due to blurring of the resolution target. However, the GSD (Ground Sample Distance) of orthoimage excluding low quality images was 3.2cm with a Bar target and 4.0cm with a Siemens star thanks to the clear resolution targets. It therefore demonstrates the practicality of the proposed sharpness analysis method in this study.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.3-8
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• 2016

Due to the recent technical development and the enhancement of image resolution, Unmanned Airborne Vehicles(UAVs) have been used for various fields. A low altitude UAV system takes advantage of taking riverbed imagery at small rivers as well as land surface imagery on the ground. The bathymetric data are generated from the low altitude UAV system. The accuracy of the data is analyzed along water depths, comparing GPS observations and a DSM generated from UAV images. It is found that the depth accuracy of the geospatial data below 50 cm depth of water satisfies the regulation(${\pm}10cm$ spatial accuracy) of bathymetric surveying. Therefore this research shows that the geospatial data generated from UAV images at shallow regions of rivers can be used for bathymetric surveying.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.127-137
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• 2018

Recently, UAVs and Drones have been used for various applications. In particular, in the field of surveying, there are studies on the technology for monitoring the terrain based on the high resolution image data obtained by using the UAV-equipped digital camera or various sensors, or for generating high resolution orthoimage, DSM, and DEM. In this study, we analyzed the accuracy of GCP(Ground control point) matching using UAV and VRS-GPS. First, we used VRS-GPS to pre-empt the ground reference point, and then imaged at a base altitude of 150m using UAV. To obtain DSM and orthographic images of 646 images, RMSE was analyzed using pix4d mapper version As a result, even if the number of GCP matches is more than five, the error range of the national basic map(scale : 1/5,000) production work regulations is observed, and it is judged that the digital map revision and gauging work can be utilized sufficiently.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1013-1025
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• 2020

Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.445-446
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• 2018

최근 무인항공기 (Unmanned Aerial Vehicle, UAV)에 장착한 카메라를 활용하여 사용자의 눈높이가 아닌 새로운 시각에서 사용자를 촬영한 영상을 제공한다. 사용자를 추적하며 촬영하기 위해 저전력 블루투스 (Bluetooth Low Energy, BLE) 신호, 영상, 그리고 Natural User Interface/Natual User Experience(NUI/NUX) 기술을 활용한다. BLE 신호로 사용자를 추적하는 경우 사용자의 후방에서 추적하며 사용자만을 추적하며 촬영 가능한 문제가 있다. 하지만 복수의 사용자를 전방에서 추적하며 촬영하는 방법이 필요하다. 본 논문에서는 복수의 사용자를 추적하며 전방에서 촬영하기 위해 UAV의 비행방향을 결정하는 방법을 설명한다. 복수의 사용자로부터 측정 가능한 BLE 신호들을 UAV에서 측정한다. 복수개의 BLE 신호의 변화를 활용하여 UAV의 비행방향을 결정한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.217-226
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• 2022

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σ_MTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.317-325
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• 2020

UAV (Unmanned Aerial Vehicle) photogrammetry has recently emerged as a means of obtaining highly precise and rapid spatial information due to its cost-effectiveness and high efficiency. However, current procedures or regulations for quantitative quality verification methods and certification processes for UAV-images are insufficient. In addition, the current verification method for image quality is not evaluated by an MTF (Modulation Transfer Function) analysis or edge response analysis, which can analyze the degree of contrast including image resolution, and only relies on the GSD (Ground Sample Distance) analysis. Therefore, in this study, the edge response analysis using a Slanted edge target was performed along with GSD analysis to confirm the necessity of analyzing edge response analysis in UAV-images quality analysis. Furthermore, a Matlab GUI-based software tool was developed to help streamline the edge response analysis. As a result, we confirmed the need for edge response analysis since the outputs of the edge response analysis from the same GSD had significantly different outcomes. Additionally, we found that the quality of the edge response analysis of UAV-images is proportional to the performance of the camera mounted on the UAV.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1343-1351
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• 2014

Recent technological advances in wireless networks and microelectromechanical systems (MEMS) have led to the development of different types of mini-UAVs and their utilizations in various ways. This study endeavors to develop a low-cost mini-UAV with autonomous flight capability, in order to obtain geospatial information of a small or medium-sized area, and also assess its flight stability by comparing the predetermined flight paths against the actual flight paths. Based on a post-development flight test, stable flight has been proven achievable as follows: the maximum endurance speed is 1 hour, the flying distance is 50km, the horizontal accuracy of flight paths is about ${\pm}6{\sim}8m$, and the altitude accuracy is about ${\pm}8m$. Therefore, it is deemed that high-resolution images which can be utilized for geospatial information are obtainable. This indicates that a UAV flying at an altitude of 200m can acquire images across a $2km{\times}3km$ area on the ground within 25 minutes, which validates its high usability for obtaining high-solution images at low altitudes in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.7
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• pp.582-589
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• 2012

This paper describes the algorithm recognizing car type from the image received from UAV and the recognition results between three types of car images. Using the NCC(Normalized Cross-Correlation) algorithm, geometric information is matched from template images. Template images are obtained from UAV and satellite map and indoor experiment is performed using satellite map. After verification of the possibility, experiment for verification of same car type recognition is performed using small UAV. In the experiment, same type cars are matched with 0.6 point similarity and truck with similar color distribution is not matched with template image of a sedan.