• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.475-488
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• 2018

Surveying urban tributary vegetation is based mainly on field sampling at present. The tributary vegetation survey integrating UAV NIR(Unmanned Aerial Vehicle Near Infrared Radiance) imagery and in-situ point photo has received only limited attentions from the field ecologist. The reason for this could be the largely undemonstrated applicability of UAV NIR imagery by the field ecologist as a monitoring tool for urban tributary vegetation. The principal advantage of UAV NIR imagery as a remote sensor is to provide, in a cost-effective manner, information required for a very narrow swath target such as urban tributary (10m width or so), utilizing very low altitude flight, real-time geo-referencing and stereo imaging. An exhaustive and realistic comparison of the two techniques was conducted, based on operational customer requirement of urban tributary vegetation survey: synoptic information, ground detail and quantitative data collection. UAV NIR imagery made it possible to identify area-wide patterns of the major plant communities subject to many different influences (e.g. artificial land use pattern), which cannot be acquired by traditional field sampling. Although field survey has already gained worldwide recognition by plant ecologists as a typical method of urban tributary vegetation monitoring, this approach did not provide a level of information that is either scientifically reliable or economically feasible in terms of urban tributary vegetation (e.g. remedial field works). It is anticipated that this research output could be used as a valuable reference for area-wide information obtained by UAV NIR imagery in urban tributary vegetation survey.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.407-418
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• 2018

The frequency and risk of disasters are increasing due to environmental and social factors. In order to respond effectively to disasters that occur unexpectedly, it is very important to quickly obtain up-to-date information about target area. It is possible to intuitively judge the situation about the area through the image-map generated at high speed, so that it can cope with disaster quickly and effectively. In this study, we propose an image-map generation and visualization system from UAV images for real-time disaster monitoring. The proposed system consists of aerial segment and ground segment. In the aerial segment, the UAV system acquires the sensory data from digital camera and GPS/IMU sensor. Communication module transmits it to the ground server in real time. In the ground segment, the transmitted sensor data are processed to generate image-maps and the image-maps are visualized on the geo-portal. We conducted experiment to check the accuracy of the image-map using the system. Check points were obtained through ground survey in the data acquisition area. When calculating the difference between adjacent image maps, the relative accuracy was 1.58 m. We confirmed the absolute accuracy of the image map for the position measured from the individual image map. It is confirmed that the map is matched to the existing map with an absolute accuracy of 0.75 m. We confirmed the processing time of each step until the visualization of the image-map. When the image-map was generated with GSD 10 cm, it took 1.67 seconds to visualize. It is expected that the proposed system can be applied to real - time monitoring for disaster response.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.145-154
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• 2014

The road network becomes more complex and extensive. Therefore, the inconveniences are caused in accordance with the time delay of the restoration of damaged roads, demands for excessive costs on information collection, and limitations on acquisition of damage information of the roads. Recently, road centric spatial information is gathered using mobile multi sensor system for road inventory. But expensive MMS(Mobile Mapping System) equipments require high maintenance costs from beginning and takes a lot of time in the data processing. So research is needed for continuous maintenance by collecting and displaying the damaged information on a digital map using low cost mobile camera system. In this research we aim to develop the techniques for mosaic with a regular ground sample distance using successive image from oblique camera on a vehicle. For doing this, mosaic image is generated by estimating the homography of high resolution oblique image, and the ground sample distance and appropriate overlap are analyzed using high resolution aerial oblique images which contain resolution target. Based on this we have proposed the appropriate overlap and exposure interval for mobile road inventory system.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.61-68
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• 2016

Digital aerial images have been commonly used in a large scale map production owing to their excellent geometry, and high spatial and radiometric resolution in recent years. However, a quality verification process for acquired images should be preceded in order to secure the high precision and reliability of produced results. Several experimental studies to verify digital imaging systems have been vigorously researched by constructing permanent test field in abroad. On the other hand, it is urgently necessary to suggest a practical scheme for an image quality verification, because this related study and experiment are still in its early stage at home. Hence, this study aims to present an easy method to measure the spatial resolution of the image in a visual way using a portable Siemens star. The images used in the study were obtained with three different cameras, two frame array sensors of DMC, UltraCamXp and a linear array sensor of ADS80. The Siemens star target appeared in every image is extracted and then the spatial resolution of image is compared with theoretical GSD(Ground Sample Distance) by a visual method. In addition, the change of spatial resolution depending on the location of the Siemens star from image center and flight direction and cross-flight direction is also compared and analyzed. As study results, while the theoretical GSDs of images taken with each camera are about 6~9cm, the visual resolutions are 1.2~1.3 times as great as the theoretical ones.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.4
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• pp.35-44
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• 2016

Two primary tools to study park use are surveys and direct observation. Existing methods, however, are limited in terms of considerable costs in both time and money and the personal bias of respondents or observers. These limitations result in a lack of efficient, reliable, and affordable tools to investigate park use. This study explores the reliability and usability of unmanned aerial vehicles(UAVs) to explore park use in urban parks in Busan metropolitan city. By comparing with a systematic observation tool, SOPARC(System for Observing Play and Recreation in Communities), this study finds that the number of park users observed by two different techniques are highly correlated and not significantly different with each other. In addition, both methods show a high level of test-retest reliability. Comparing to existing methods, the UAV-using observation tool could cover larger target areas and is suitable to count park users in a more reliable and efficient way and map their use patterns, although it is weak in collecting detailed user information and surveying under poor conditions such as rain. Thus, the UAV method could complement direct observation. This study suggests practical implications of a UAV method to study park use.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.35-42
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• 2021

The purpose of this paper is to review the small unmanned aerial system (sUAS) safety policy promoted by the United States(US) government. Therefore, in this paper, along with sUAS risk factors, the risk factors of sUAS that the US government is interested in are described. In addition, the risk factors were classified into physical and non-physical factors, and provisions mentioned in the Federal Aviation Administration(FAA) Relicensing Act were reviewed. Other risk scenarios were analyzed focusing on target scenario items that the FAA is interested in, such as flight operation disruption, infrastructure damage, and facility trespassing. Of course, we looked at the risk management principles promoted by the US FAA. In this paper, as a research method, the direction and contents of the FAA's sUAS policy were studied and reviewed from the analysis of major foreign journals and policy. In the research result of this paper, by analyzing the FAA sUAS safety risk management policy, the integrated operation and safety policy, physical risk management policy, operation and safety regulation, and sUAS policy and technology direction necessary for establishing the sUAS safety risk management guide in Korea are presented. The contribution of this study is to identify the leading US sUAS safety policy direction, and it can be used as basic data for deriving future domestic policy directions from this. Based on the research results presented in the future, policy studies are needed to derive detailed implementation plans.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1479-1488
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• 2022

Accidents in which oil spills occur intermittently in the ocean due to ship collisions and sinkings. In order to prepare prompt countermeasures when such an accident occurs, it is necessary to accurately identify the current status of spilled oil. To this end, the Coast Guard patrols the target area with a fixed-wing airplane or helicopter and checks it with the naked eye or video, but it was difficult to determine the area contaminated by the spilled oil and its exact location on the map. Accordingly, this study develops a technology for direct ortho-rectification by automatically geo-referencing aerial images collected by the Coast Guard without individual ground reference points to identify the current status of spilled oil. First, meta information required for georeferencing is extracted from a visualized screen of sensor information such as video by optical character recognition (OCR). Based on the extracted information, the external orientation parameters of the image are determined. Images are individually orthorectified using the determined the external orientation parameters. The accuracy of individual orthoimages generated through this method was evaluated to be about tens of meters up to 100 m. The accuracy level was reasonably acceptable considering the inherent errors of the position and attitude sensors, the inaccuracies in the internal orientation parameters such as camera focal length, without using no ground control points. It is judged to be an appropriate level for identifying the current status of spilled oil contaminated areas in the sea. In the future, if real-time transmission of images captured during flight becomes possible, individual orthoimages can be generated in real time through the proposed individual orthorectification technology. Based on this, it can be effectively used to quickly identify the current status of spilled oil contamination and establish countermeasures.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.663-668
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• 2023

Recently it is very important to collect information such as enemy positions and facilities. To this end, unmanned aerial vehicles such as multicopters have been actively developed, and various mission equipment mounted on unmanned aerial vehicles have also been developed. The coordinate-oriented algorithm refers to an algorithm that calculates a gaze angle so that the mission equipment can fix the gaze at a desired coordinate or position. Flight data and GPS data were collected and simulated using Matlab for coordinate-oriented algorithms. In the simulation using only the coordinate data, the average Pan axis angle was about 0.42°, the Tilt axis was 0.003°~0.43°, and the relatively wide error was about 0.15° on average. As a result of converting this into the distance in the NE direction, the error distance in the N direction was about 2.23m on average, and the error distance in the E direction was about -1.22m on average. The simulation applying the actual flight data showed a result of about 19m@CEP. Therefore, we conducted a study on the self-error of coordinate-oriented algorithms in monitoring and information collection, which is the main task of EOTS, and confirmed that the quantitative target of 500m is satisfied with 30m@CEP, and showed that the desired coordinates can be directed.

• Korean journal of applied entomology
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• v.57 no.2
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• pp.69-75
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• 2018

Bactrocera depressa and B. scutellata are serious insect pests to pumpkin in Korea. Adult stage which exposes to aerial condition is the optimal target for control because the immature stages of both species hide within host fruit, flowers or under ground. This study aimed to develop an attract-to-kill technique of their females. A commercially available attract-to-kill agent was not effective to attract these two pumpkin fruit flies. This study developed an attractant containing protein-based terpinyl acetate (TA). This TA-protein lure was effective to attract two pumpkin fruit flies. It attracted both sexes with female-biased frequency (60-70%). This TA-protein lure would be used for control both pumpkin fruit flies and may be used for monitoring field populations of B. depressa, in which specific attractant is not known.