• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.11-19
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• 2012

Due to existing infrastructure to collect traffic information was constructed to expressway and national highway, we cannot precisely know traffic situation for their surrounding area. Therefore, it is difficult to provide reliable traffic information to users using navigation and smartphone. In this research, we collected aerial images by using unmanned airship capable of wide-area monitoring and proposed a method extracting vehicle speed from the collected data. And, we performed experiments to verify the accuracy of extracted vehicle speed. Our method proposed in this research can be used to extract a new approach of traffic information according to increased demand of traffic monitoring. We expect that our method will become a new research trend in traffic information application.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1353-1357
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• 2018

This paper compares and analyzes Fusarium wilt of radish by using an unmanned aerial vehicle(UAV) with the NDVI-7 camera. The UAV have taken near-infrared images of the Radish field in Gangwon area, which is affected by Fusarium wilt. Based on those images, we analyzed NDVI(Normalized difference vegetation index) and compared conditions of radish by using the Blue value among Regular Vegetation Index in NDVI. First, the radish field is divided into three fields for radish, soil and vinyl. Each field has separate Blue values that are radish 0.4890, soil 0.2959, vinyl -0.0605 respectively. Second, radish condition levels are divided into four stages which are normal, early, middle, and late stage of Fusarium wilt. The average values of each stage are normal 0.5165(100%), early 0.4565(88%), middle 0.3444(66%), and late 0.1772(34%) respectively. This result shows that this NDVI value is validated by measuring conditions of Radish and soil.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.130-136
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• 2010

This study estimates and evaluates the parameters to relate spectral intensities of aerial and terrestrial images through spectral analysis of each band. For the experiment, an aerial image covering the headquater of the Kyungpook National University was used and terrestrial images were taken by the Sony DSC-F828 DSLR camera. For finding the spectral correspondence, gray intensity, RGB variance, mean, standard deviation were computed, from which parameters of a linear model between patches of both images were computed and evaluated using check patches.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.171-179
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• 2010

Effective monitoring and maintenance operation of towers, power lines and other defects to ensure high quality and reliability of electric power supplied to customers is becoming one of the most important tasks of today's power industry. One specific technology that has the potential to automate the entire surveillance process is unmanned aerial vehicles. In this paper, we propose a new power line extraction method using the directivity of a power line and Hough transform to detect efficiently power lines from thermal aerial images. In simulation results for several aerial images, the proposed method shows good performance in extracting power line detection.

• Korean Journal of Agricultural Science
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• v.42 no.3
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• pp.269-276
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• 2015

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we discussed the state-of-the-art of the domestic and international use of UAV in agricultural sector as well as assessed its utilization and applicability for agricultural environment in Korea. Association of robotic, computer vision and geomatic technologies have established a new paradigm of low-altitude aerial remote sensing that has now been receiving attention from researchers all over the world. In a field study, it has been found that use of UAV imagery in an agricultural subsidy program can reduce the farmers' complain and provide objective evidence. UAV high resolution photography can also be helpful in monitoring the disposal zone for animal carcasses. Due to its expeditiousness and accuracy, UAV imagery can be a very useful tool to evaluate the damage in case of an agricultural disaster for both parties insurance companies and the farmers. Also high spatial and temporal resolution in UAV system can increase the prediction accuracy which in turn help to maintain the agricultural supply and demand chain.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.471-477
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1cm, ${\pm}$24.7cm, ${\pm}$35.9cm, respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.663-670
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• 2020

In the present study, we assessed the accuracy of aerial triangulation using a UAV (Unmanned Aerial Vehicle) capable of network RTK (Real-Time Kinematic) survey in a disaster situation that may occur in a semi-urban area mixed with buildings. For a reliable survey of check points, they were installed on the roofs of buildings, and static GNSS (Global Navigation Satellite System) survey was conducted for more than four hours. For objective accuracy assessment, coded aerial targets were installed on the check points to be automatically recognized by software. At the instance of image acquisition, the 3D coordinates of the UAV camera were measured using VRS (Virtual Reference Station) method, as a kind of network RTK survey, and the 3-axial angles were achieved using IMU (Inertial Measurement Unit) and gimbal rotation measurement. As a result of estimation and update of the interior and exterior orientation parameters using Agisoft Metashape, the 3D RMSE (Root Mean Square Error) of aerial triangulation ranged from 0.153 m to 0.102 m according to the combination of the image overlap and the angle of the image acquisition. To get higher aerial triangulation accuracy, it was proved to be effective to incorporate oblique images, though it is common to increase the overlap of vertical images. Therefore, to conduct a UAV mapping in an urgent disaster site, it is necessary to acquire oblique images together rather than improving image overlap.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.143-149
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• 2014

The Disaster planning for the reservoir should be more quickly and intuitively establish measures by means of the sequential monitoring of change status of the reservoir water level and water surface area. This paper presents an approach using the orthophoto image produced by the periodic unmanned aerial photogrammetry and analyzed the feasibility. Total three time of unmanned aerial survey were conducted to make orthophoto images for the Seongnae reservoir and we analyzed the amount of changes for water level and surface area compare with each images. As the Analysis results, it was possible to effectively observe the increase in the water level rises and the surface area due to the rainfall. The maximum deviations of orthophoto images was 7.5cm in X-direction, 10.8cm in Y-direction and 14.1cm in elevation compare with ground surveying results. Therefore, we conclude that the unmanned aerial photogrammetry could be applied with comprehensive reservoir monitoring works for disaster management for reservoir in the future. And, the orthophoto production takes about two hours to shoot the images, and approximately four hours is considered for the image processing. So, the unmanned aerial photogrammetry is considered to be the best disaster work that requires urgent because analysis is possible in the shooting day.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_3
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• pp.1191-1197
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• 2022

Recently, many studies have been conducted to utilize the digital aerial photogrammetry method in the field of cadastral surveying. The representative models of digital cameras currently used for aerial photogrammetry are classified into line-type and convex-type cameras, so the representative models were selected and analyzed. The purpose of this study was to analyze whether the accuracy suggested by the cadastral survey enforcement rules was satisfied by comparing the orthogonal and ortho image performance. As a result, there were some representative false points that exceeded the acceptable range, but the results extracted from most of the images were shown to satisfy the acceptable range. Therefore, it can be said that the application of digital aerial photogrammetry to the cadastral field in the technical aspect has sufficient potential.