• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.461-471
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• 2015

In this study, we generated orthoimages and Digital Elevation Model (DEM) from Unmanned Aerial Vehicle (UAV) to confirm the accuracy of possibility of geospatial information system generation, then compared the DEM with the topographic height values measured from Real Time Kinematic-GPS (RTK-GPS). The DEMs were generated from aerial triangulation method using fixed-wing UAV and rotary-wing UAV, and DEM based on the waterline method also generated. For the accurate generation of mosaic images and DEM, the distorted images occurred by interior and exterior orientation were corrected using camera calibration. In addition, we set up the 30 Ground Control Points (GPCs) in order to correct of the UAVs position error. Therefore, the mosaic images and DEM were obtained with geometric error less than 30 cm. The height of generated DEMs by UAVs were compared with the levelled elevation by RTK-GPS. The value of R-square is closely 1. From this study, we could confirm that accurate DEM of the tidal flat can be generated using UAVs and these detailed spatial information about tidal flat will be widely used for tidal flat management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.53-62
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• 2016

In recent years, UAV Photogrammetry based on an ultra-light UAS(Unmanned Aerial System) installed with a low-cost compact navigation device and a camera has attracted great attention through fast and accurate acquirement of geo-spatial data. In particular, UAV Photogrammetry do gradually replace the traditional aerial photogrammetry because it is able to produce DEMs(Digital Elevation Models) and Orthophotos rapidly owing to large amounts of high resolution image collection by a low-cost camera and image processing software combined with computer vision technique. With these advantages, UAV-Photogrammetry has therefore been applying to a large scale mapping and cadastral surveying that require accurate position information. This paper presents experimental results of an accuracy performance test with images of 4cm GSD from a fixed wing UAS to demarcate parcel boundaries in agricultural area. Consequently, the accuracy of boundary point extracted from UAS orthoimage has shown less than 8cm compared with that of terrestrial cadastral surveying. This means that UAV images satisfy the tolerance limit of distance error in cadastral surveying for the scale of 1: 500. And also, the area deviation is negligible small, about 0.2%(3.3m²), against true area of 1,969m² by cadastral surveying. UAV-Photogrammetry is therefore as a promising technology to demarcate parcel boundaries.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.9
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• pp.16-26
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• 2005

The aerodynamic design of a proprotor for the Smart UAV adopting tiltrotor aircraft concept is conducted in this study. Since proprotor of tiltrotor aircraft is operated at both rotary and fixed wing mode with single configuration rotor, the proprotor has to be designed to meet performance requirements for both flight modes. The aerodynamic design of proprotor is accomplished by combining three sources of data - the proprotor performance data, the aerodynamic data of vehicle, and the performance data of engine. The performance analysis code for proprotor is based on the combined momentum and blade element theory and validated by comparison with the TRAM data. In order to design configuration for a proprotor satisfying requirements for both rotary and fixed wing mode, various kind of performance maps are constructed for many performance and configuration parameters. From the analysis the twist angle of 38 degrees and the solidity of 0.118 are decided to be the optimal geometric parameters for both operating conditions.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.910-919
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• 2012

In this paper, we described development of on-board image processing system and its process and verified its performance through flight experiment. The image processing board has single ARM(Advanced Risk Machine) processor. We performed Embedded Linux Porting. Algorithm to be applied for object tracking is color-based image processing algorithm, it can be designed to track the object that has specific color on ground in real-time. To verify performance of the on-board image processing system, we performed flight test using the PNUAV, UAV developed by LAB. Also, we performed optimization of the image processing algorithm and kernel to improve real-time performance. Finally we confirmed that proposed system can track the blue-color object within four pixels error range consistently in the experiment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.6
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• pp.478-487
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• 2014

The simplified performance analysis and initial configuration design are required for the successful development of UAV during the conceptual design, in which empirical formulas and trend equations are utilized for the UAV performance analysis. In the conceptual design phase various UAV configurations may be considered, however, it is very inefficient and unnecessary to consider all configurations for the conceptual design. In this study, the database for the fixed wing UAVs whose MTOW is between 50kg and 1,500kg was also constructed for the selection of configuration frequently used. The parametric analyses were performed for major performance parameters, and trend equations were developed through regression analyses for these individual performance parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.129-136
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• 2012

In the US, Japan and Germany the Aerial-Based Vehicle Detection System, which collects real-time traffic data using the Unmanned Aerial Vehicle (UAV), helicopters or fixed-wing aircraft has been developed for the last several years. Therefore, this study was done to find out whether the Aerial-Based Vehicle Detection System could be used for real-time traffic data collection. For this purpose the study was divided into two parts. In the first part the possibility of retrieving real-time traffic data such as travel speed from the aerial photographic image using the image processing technique was examined. In the second part the quality of the retrieved real-time traffic data was examined to find out whether the data are good enough to be used as traffic information source. Based on the results of examinations we could conclude that it would not be easy for the Aerial- Based Vehicle Detection System to replace the present Vehicle Detection System due to technological difficulties and high cost. However, the system could be effectively used to make the emergency traffic management plan in case of incidents such as abrupt heavy rain, heavy snow, multiple pile-up, etc.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.183-188
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• 2017

As the price of small UAVs is getting cheaper and its controllability is getting greatly increased, many aerial applications using both fixed-wing and hoverable UAVs have appeared in recent years. In this paper, a new aerial advertising method is proposed using four hoverable UAVs. Using the UAV swarm control method, four UAVs are maneuvered to carry a $7.07{\times}7.07m^2$ square banner along collision-free and predefined waypoints for aerial advertising. According to simulation results, it takes about 270 s for UAVs to perform aerial advertising in $669{\times}669m^2$ size area and the minimum distance among UAVs turns out to be 0.45 m which proves there is no any collision. Due to abrupt direction changes of UAVs along the predefined waypoints, UAVs cannot always maintain exact square formation and it results the maximum and minimum side lengths of square formation to be 10.35 m and 1.96 m, respectively. Also, the maximum and minimum diagonal lengths of square formation turn out to be 14.75 m and 2.78 m, respectively.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.501-509
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• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.24-33
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• 2018

DSM and orthoimage, which are representative results of UAV photogrammetry, are high-quality spatial information data and are widely used in various fields of spatial information industry in recent years. However, the UAV photogrammetry has a problem that the quality of the output of the UAV deteriorates due to the altitude of the UAV, the camera calibration, the weather conditions at the time of shooting, the performance of the GPS / IMU and the number of the ground reference points. The purpose of this study is to analyze the location accuracy of unmanned aerial photogrammetry according to the change of the number if ground control points. Experiments were made with fixed wing, and the shooting altitude was set at 130m and 260m. The number of ground reference points used was 9, 8, 5, and 4, respectively. Ten checkpoints were used. XY RMSE for orthoimage and Z RMSE for DSM were compared and analyzed. In addition, the resolution of the orthoimage was determined to affect the judgment of the operator in the verification of the planimetric position accuracy, and the visual resolution was analyzed using the Siemens star target. As a result of the analysis, the variation of the vertical position accuracy is larger than the variation of the planimetric position accuracy when the number of the ground reference points are different. Also The higher the flying height, the greater the effect of change of ground control points on position accuracy.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.75-86
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• 2020

The purpose of this study is to develop a technology for estimating rice growth and damage effect according to bacterial leaf blight using UAV multi-spectral imagery. For this purpose, we analyzed the change of aerial images, rice growth factors (plant height, dry weight, LAI) and disease effects according to disease occurrence by using UAV images for 3 rice varieties (Milyang23, Sindongjin-byeo, Saenuri-byeo) from 2017 to 2018. The correlation between vegetation index and rice growth factor during vegetative growth period showed a high value of 0.9 or higher each year. As a result of applying the growth estimation model built in 2017 to 2018, the plant height of Milyang23 showed good error withing 10%. However, it is considered that studies to improve the accuracy of other items are needed. Fixed wing unmanned aerial photographs were also possible to estimate the damage area after 2 to 4 weeks from inoculation. Although sensing data in the multi-spectral (Blue, Green, Red, NIR) band have limitations in early diagnosis of rice disease, for rice varieties such as Milyang23 and Sindongjin-byeo, it was possible to construct the equation of infected leaf area ratio and rice yield estimation using UAV imagery in early and mid-September with high correlation coefficient of 0.8 to 0.9. The results of this study are expected to be useful for farming and policy support related to estimating rice growth, rice plant disease and yield change based on UAV images.