• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.485-491
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• 2008

LiDAR systems are usually incorporated a laser scanner and GPS/INS modules with a digital aerial camera. LiDAR point clouds and digital aerial images acquired by the systems provide complementary spatial information on the ground. In addition, some of laser scanners provide intensity, radiometric information on the surface of the earth. Since the intensity is unnecessary of registration and provides the radiometric information at a certain wavelength on the location of LiDAR point, it can be a valuable ancillary information but it does not deliver sufficient radiometric information compared with digital images. This study utilize the LiDAR points as ground control points (GCPs) to adjust exterior orientations(EOs) of the stereo images. It is difficult to find exact point of LiDAR corresponding to conjugate points in stereo images, but this study used intensity of LiDAR as an ancillary data to find the GCPs. The LiDAR points were successfully used to adjust EOs of stereo aerial images, therefore, successfully provided the prerequisite for the precise registration of the two data sets from the LiDAR systems.

• Journal of Power System Engineering
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• v.20 no.3
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• pp.64-73
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• 2016

In this research work, an algorithm development on tracking end-point of aerial work platform with jib profile and bend-linked boom was carried out to find the X, Y and Z direction value using coordinate transformation matrix. This matrix consists of device status value(length and angle) based on camera position axis, which are sent from device controller PLUS+1 by CAN protocol. These values are used to measure the distance and angle from the camera to the end-point. Using these distance and angle value, monitoring system controls FAN/TILT/ZOOM status of camera to get an adequate scene of workplace. This program was written in Java, C# and C for mobile device. These results provide the information to the aerial work device for secure operation.

• 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.

• Spatial Information Research
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• v.19 no.4
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• pp.21-31
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• 2011

As large scaled natural or man-made disasters being increased, the demand for rapid responses for such emergent situations also has been ever-increasing. These responses need to acquire spatial information of each individual site rapidly for more effective management of the situations. Therefore, we are developing a close-range real-time aerial monitoring system based on a low altitude unmanned helicopter. This system can acquire airborne sensory data in real-time and generate rapidly geospatial information. The system consists of two main parts: aerial and ground parts. The aerial part includes an aerial platform equipped with multi-sensor(cameras, a laser scanner, a GPS receiver, an IMU) and sensor supporting modules. The ground part includes a ground vehicle, a receiving system to receive sensory data in real-time and a processing system to generate the geospatial information rapidly. Development and testing of the individual modules and subsystems have been almost completed. Integration of the modules and subsystems is now in progress. In this paper, we w ill introduce our system, explain intermediate results, and discuss expected outcome.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.440-446
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• 2019

Pine wilt disease occurred for the first time in Busan in 1988 and the damage has since been increasing. In 2005, a special law was enacted for pine wilt disease by Korea Forest Service. Incidences relating to the forest pest had been frequent and chemical control as well as physical control techniques had been applied to control it. Therefore, there is a need to reduce the damage caused by the pine wilt disease through intensive management such as continuous monitoring, control, and monitoring based on active control as well as management measures. In this study, the UAV-based monitoring method was proposed as an economical way of monitoring the forest pest. The efficiency of the existing method and UAV method had been analyzed, and as a result the study suggested that UAV can be used for forest pest monitoring and indeed improve efficiency. The UAV-based forest pest monitoring method has a cost reduction of about 50% compared with the conventional method and will also help to reduce the area where the survey was omitted.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.432-440
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• 2017

In this paper, we propose a jellyfish distribution recognition and monitoring system using a UAV (unmanned aerial vehicle). The UAV was designed to satisfy the requirements for flight in ocean environment. The target jellyfish, Aurelia aurita, is recognized through convolutional neural network and its distribution is calculated. The modified deep neural network architecture has been developed to have reliable recognition accuracy and fast operation speed. Recognition speed is about 400 times faster than GoogLeNet by using a lightweight network architecture. We also introduce the method for selecting candidates to be used as inputs to the proposed network. The recognition accuracy of the jellyfish is improved by removing the probability value of the meaningless class among the probability vectors of the evaluated input image and re-evaluating it by normalization. The jellyfish distribution is calculated based on the unit jellyfish image recognized. The distribution level is defined by using the novelty concept of the distribution map buffer.

• Journal of Biosystems Engineering
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• v.25 no.3
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• pp.233-240
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• 2000

A commercially available Doppler radar was modified and evaluated for on-board monitoring of ground speed. The radar output was corrected for pitch angle of aircraft based on the output of an electrolytic tilt sensor. The effects of aircraft speed, height and mounting angle on error in the ground speed were evaluated. The speed error decreased with an increase of the mounting angle since the radar contact angle with respect to the ground approached to the mounting angle. The error increased with an increase of the nominal aircraft speed. The altitude insignificantly affected the speed error. The Doppler radar provided acceptable percent errors within 5% in most measurements. The error can be reduced within ${\pm}$1.5% by increasing the mounting angle ($43^{\circ}$). The error of -3.8% at the mounting angle of $29^{\circ}$could be reduced by adjusting the mounting angle with respect to the radar contact angle.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.3
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• pp.225-231
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• 2015

Improving current pasture productivity by precision management requires practical tools to collect site specific pasture biomass data. Recent developments in unmanned aerial vehicle (UAV) technology provide cost effective and real time applications for site specific data collection. For the mapping of herbage biomass (BM) on a hill pasture, we tested a UAV system with digital cameras (visible and near-infrared (NIR) camera). The field measurements were conducted on the grazing hill pasture at Hanwoo Improvement Office, Seosan City, Chungcheongnam-do Province, Korea on May 17 and June 27, 2014. Plant samples were obtained from 28 sites. A UAV system was used to obtain aerial photos from a height of approximately 50 m (approximately 30 cm spatial resolution). Normalized digital number (DN) values of Red and NIR channels were extracted from the aerial photos and a normalized differential vegetation index using DN ($NDVI_{dn}$) was calculated. The results show that the correlation coefficient between BM and $NDVI_{dn}$ was 0.88. For the precision management of hilly grazing pastures, UAV monitoring systems can be a quick and cost effective tool to obtain site-specific herbage BM data.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.77-84
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• 2022

In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.