• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.708-713
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• 2013

KARI is developing a solar-electric powered HALE UAV(EAV-3). For demonstrating the technology, EAV-2H, a down-scaled version of EAV-3, is developed and after EAV-2H's initial flight test, the directional stability and control need to be improved. Thus, the vertical tail and rudder of EAV-2H are redesigned with Advanced Aircraft Analysis(AAA). Size of the rudder is increased from mean chord ratio of rudder to vertical tail, $C_r/C_v(%)=30$ to $C_r/C_v(%)=60$ and size of the vertical tail is reduced 15%. As a result, the directional control to side wind($v_1$) is improved to sideslip angle, ${\beta}(deg)=25^{\circ}$ and $v_1(m/sec)=3.54$. Also, variation of airplane side force coefficient with sideslip angle ($C_{y_{\beta}}$) and variation of airplane side force coefficient with dimensionless rate of change of yaw rate ($C_{y_r}$) are reduced 15% and 22%, respectively to minimize the effect of side wind. The empennage design of EAV-2H is verified with flight tests and applied to design of KARI's solar-electric-powered EAV-3.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.809-819
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• 2020

In this study, the twist angle and wing planform shapes were selected as design variables and optimized to secure the stability of the flying-wing type UAV. Flying-wing aircraft has no separated fuselage and tails, which has advantages in aerodynamic characteristics and stealth performance, but it is difficult to secure the flight stability. In this paper, the sweep back angle and twist angle were optimized to obtain the lateral stability, the static margin and wing planform shapes were optimized to improve the longitudinal stability of the flying-wing, then effect of the twist angle was confirmed by comparing the stability of the shape with the winglet and the shape with the twist angle. In the optimization formulation, focusing on improving stability, constraints were established, objective functions and design variables were set, then design variable sensitivity analysis was performed using the Sobol method. AVL was used for aerodynamic analysis and stability analysis, and SQP was used for optimization. The CFD analysis of the optimized shape and the simulation of the dynamic stability proved that the twist angle can be applied to the improvement of the lateral stability as well as the stealth performance in the flying-wing instead of the winglet.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1731-1738
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• 2021

The objective of this study was to extract individual trees and tree heights using UAV drone images. The study site was Gongju national university experiment forest, located in Yesan-gun, Chungcheongnam-do. The thinning intensity study sites consisted of 40% thinning, 20% thinning, 10% thinning and control. The image was filmed by using the "Mavic Pro 2" model of DJI company, and the altitude of the photo shoot was set at 80% of the overlay between 180m pictures. In order to prevent image distortion, a ground reference point was installed and the end lap and side lap were set to 80%. Tree heights were extracted using Digital Surface Model (DSM) and Digital Terrain Model (DTM), and individual trees were split and extracted using object-based analysis. As a result of individual tree extraction, thinning 40% stands showed the highest extraction rate of 109.1%, while thinning 20% showed 87.1%, thinning 10% showed 63.5%, and control sites showed 56.0% of accuracy. As a result of tree height extraction, thinning 40% showed 1.43m error compared with field survey data, while thinning 20% showed 1.73 m, thinning 10% showed 1.88 m, and control sites showed the largest error of 2.22 m.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.231-236
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• 2021

The Aphid, Myzus persicae, and the bean bug, Riptortus clavatus, are major insects in crops. This study examined the insecticide susceptibility and phytotoxicity of insecticides dispersed using an Unmanned Aerial Vehicle (UAV, multi-copter) against the insects. Sulfoxaflor suspension concentrate (SC, 16X) on potato fields and etofenprox, methoxyfenzide suspo-emulsion(SE, 8X) on soybean fields were dispersed after deploying water-sensitive paper within the field to measure the distribution pattern and coverage index of the falling insecticide. Both insecticides showed a controlled mortality of 76.4% against aphids and 97.5% and 94.4% against the 2nd nymphal, and 5th nymphal stage of the bugs, respectively. The droplet distribution was less than 0.5mm, and coverage analysis revealed an inside and outside coverage of 3.1 and 1.6, respectively. The surrounding area was affected by insecticide spraying using a multi-copter. This study is expected to help expand UAV control and use it safely in the future.

• Conservation Science in Museum
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• v.24
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• pp.55-74
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• 2020

The Sacred Bell of Great King Seongdeok is required digital precision recording of conservation conditions because of corrosion and partial abrasion of its patterns and inscriptions. Therefore, this study performed digital documentation of the bell using four types of scanning and unmanned aerial vehicle (UAV) photogrammetry technologies, and performed the various shape analyses through image processing. The modeling results of terrestrial laser scanning and UAV photogrammetry were merged and utilized as basic material for monitoring earthquake-induced structural deformation because these techniques can construct mutual spatial relationships between the bell and its tower. Additionally, precision scanning at a resolution four to nine times higher than that of the previous study provided highly valuable information, making it possible to visualize the patterns and inscriptions of the bell. Moreover, they are well-suited as basic data for identifying surface conservation conditions. To actively apply three-dimensional scanning results to the conservation of the original bell, the time and position of any changes in shape need to be established by further scans in the short-term. If no change in shape is detected by short-term monitoring, the monitoring should continue in medium- and long-term intervals.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.4
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• pp.295-301
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• 2021

In this study we developed the ground-based multispectral camera system to determine proper period to build and apply the calibration equation for dry matter of winter forage corps monitoring by unmanned aerial vehicle (UAV). Normalized difference vegetation index (NDVI) of rye, whole barley and Italian ryegrass (IRG) were measured and the growth period was divide by NDVI increasing period and decreasing period. Day of the maximum NDVI value of rye, whole barley and IRG were 8th, 9th and 5th April 2020. Regression analysis showed that the correlation coefficients (R²) between dry matter and NDVI were 0.84, 0.84, 0.78 during NDVI increasing period and 0.00, 0.02, 0.27 during NDVI decreasing period. Therefore, detailed NDVI monitoring is required to determine the proper period to build and apply the calibration equation and the ground-based multispectral camera system was effective tool for detailed NDVI monitoring.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.171-187
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• 2022

Recently, the demand and development for non-face-to-face services are rapidly progressing due to the pandemic caused by the COVID-19, and attention is focused on the metaverse at the center. Entering the era of the 4th industrial revolution, Metaverse, which means a world beyond virtual and reality, combines various sensing technologies and 3D reconstruction technologies to provide various information and services to users easily and quickly. In particular, due to the miniaturization and economic increase of convergence sensors such as unmanned aerial vehicle(UAV) capable of high-resolution imaging and high-precision LiDAR(Light Detection and Ranging) sensors, research on digital-Twin is actively underway to create and simulate real-life twins. In addition, Game engines in the field of computer graphics are developing into metaverse engines by expanding strong 3D graphics reconstuction and simulation based on dynamic operations. This study constructed a mirror-world type metaverse that reflects real-world coordinate-based reality using Unreal Engine 5, a recently announced metaverse engine, with accurate 3D spatial information data of convergence sensors based on unmanned aerial system(UAS) and LiDAR. and then, spatial information contents and simulations for users were produced based on various public data to verify the accuracy of reconstruction, and through this, it was possible to confirm the construction of a more realistic and highly utilizable metaverse. In addition, when constructing a metaverse that users can intuitively and easily access through the unreal engine, various contents utilization and effectiveness could be confirmed through coordinate-based 3D spatial information with high reproducibility.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.17-27
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• 2023

Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.295-304
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• 2022

The purpose of this study is to detect the sorghum panicle using YOLOv5 based on RGB images acquired by a unmanned aerial vehicle (UAV) system. The high-resolution images acquired using the RGB camera mounted in the UAV on September 2, 2022 were split into 512×512 size for YOLOv5 analysis. Sorghum panicles were labeled as bounding boxes in the split image. 2,000images of 512×512 size were divided at a ratio of 6:2:2 and used to train, validate, and test the YOLOv5 model, respectively. When learning with YOLOv5s, which has the fewest parameters among YOLOv5 models, sorghum panicles were detected with mAP@50=0.845. In YOLOv5m with more parameters, sorghum panicles could be detected with mAP@50=0.844. Although the performance of the two models is similar, YOLOv5s ( 4 hours 35 minutes) has a faster training time than YOLOv5m (5 hours 15 minutes). Therefore, in terms of time cost, developing the YOLOv5s model was considered more efficient for detecting sorghum panicles. As an important step in predicting sorghum yield, a technique for detecting sorghum panicles using high-resolution RGB images and the YOLOv5 model was presented.