• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.21-28
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• 2017

The main goal of this paper is to assess application of UAV (Unmanned Aerial Vehicle) remote sensing and GIS based images in detection and measuring of rice field drought area in South Korea. Drought is recurring feature of the climatic events, which often hit South Korea, bringing significant water shortages, local economic losses and adverse social consequences. This paper describes the assesment of the near-realtime drought damage monitoring and reporting system for the agricultural drought region. The system is being developed using drought-related vegetation characteristics, which are derived from UAV remote sensing data. The study area is $3.07km^2$ of Wonbuk-myeon, Taean-gun, Chungnam in South Korea. UAV images were acquired three times from July 4 to October 29, 2015. Three images of the same test site have been analysed by object-based image classification technique. Drought damaged paddy rices reached $754,362m^2$, which is 47.1 %. The NongHyeop Agricultural Damage Insurance accepted agricultural land of 4.6 % ($34,932m^2$). For paddy rices by UAV investigation, the drought monitoring and crop productivity was effective in improving drought assessment method.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.29-37
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• 2016

Unmanned Aerial Vehicle (UAV) have several advantages over conventional remote sensing techniques. UAV can acquire high-resolution images quickly and repeatedly with a comparatively lower flight altitude i.e. 80~400 m nullifying the effect of extreme weather and cloud. This study discussed the use of low cost-effective UAV based remote sensing application in inspection of agricultural subsidy. The study area accrue $60.5km^2$ of Buljeong-myeon, Goesan-gun, Chungbuk in South Korea. UAV image acquired 25 times from July 25 to August 11, 2015 for 3 days. It is observed that almost 81.1 % (3,571 of 4,410 parcels) parcels are truthful whereas some parcels are incorrect or fraudulent. Surveying with UAV for agricultural subsidy instead of field stuff can reduce the required time as much as 64.8 % (19 of 54 days). Therefore, it can contribute significantly in speedy and more accurate processing of grant application and can end unfair receipt of the grant which in turn will improve customer satisfaction.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.1 s.35
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• pp.37-47
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• 2006

In the last years a low-altitude image acquisition technology has been developed in application of frequent change monitoring in urban area md speedy surveillance in disaster area. A low-altitude photogrammetric system have advantages of accurate observation and free data-acquisition time. Especially, an unmaned RC-helicopter, improving safety, durability and portability, comes into the spotlight as a built-in vehicle in close range photogrammetric application due to their capability of safe near-by observation and effective flight performance. This paper gives a methodology for generating image map by development of low cost and timesaving low-altitude photogrammetric UAV(unmaned aerial vehicles) for collecting high-resolution image data, and implement of geo-rectification and image mosaicking.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.474-480
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• 2019

We propose a method to evaluate a Modulation Transfer Function (MTF) using a circular target. In addition, a MATLAB GUI-based resolution analysis tool was developed to enhance the reliability of UAV image quality and the efficiency of the work. For this purpose, images were taken with an FC-6310 during flights at altitudes of 80 m, 120 m, and 150 m and by an iXM-100 at altitudes of 150 m, 200 m, and 400 m. The MTFs of UAV images were compared with traditional photogrammetry by measuring and analyzing MTFs on images taken by the UltraCAM Eagle Mark-2 sensor at a flight altitude of 1000 m. The results show that ${\sigma}MTF$ of the FC-6310 were 0.431(80 m), 0.524(120 m), and 0.699(150 m), and those of the iXM-100 were 0.332(150 m), 0.393(200 m), and 0.631(400 m), respectively. At the altitude of 150 m, the image quality of the iXM-100, which has a high-performance camera, was very high, and the effect of the camera performance on the image quality was confirmed. In addition, the ${\sigma}MTF$ of the UltraCAM Eagle Mark-2 was 0.711 due to the high flight altitude. This was the worst value among all UAV images. However, the ${\sigma}MTF$ of the FC-6310 at 150-m altitude was 0.699, which is almost the same as that of a manned aerial image.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.15-26
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• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.1
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• pp.21-27
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• 2016

An integrated display software platform for small UAV is developed based on parallel processing technique in this paper. When the small UAV with high-performance camera and avionic modules is employed to various surveillance-related missions, it is important to reduce the operator's workload and increase the monitoring efficiency. For this purpose, it is needed to develop an efficient monitoring software enable to manipulate the image and flight data obtained during flight within the given processing time and display them simultaneously. In this paper, we set up requirements and suggest the architecture for the software platform. The integrated software platform is implemented with parallel processing scheme. Based on AR drone, we verified that the various data are concurrently displayed by the suggest software platform.

• Aerospace Engineering and Technology
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• v.6 no.2
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• pp.245-249
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• 2007

The objective of the UAV removes the life loss of the pilot who is the maximum weak point of the manned reconnaissance aircraft, accomplishes the reconnaissance it is an aircraft for. The camera which will confirm the pilot substitution reconnaissance result which stands is necessary, we should confirm; the target which this camera probably is what. The report which described like this demand condition against the consideration fact which is necessary to the selection of the image sensory device which is a camera which with character will be applied in UAV.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.321-328
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• 2018

This paper presents an automatic target tracking flight system using a PID controller based on velocity command of a multirotor UAV. The automatic flight system includes marker based onboard target detection and an automatic velocity command generation replacing manual controller. A quad-rotor UAV is equipped with a camera and an image processing computer to detect the marker in real time and to estimate the relative distance from the target. The marker tracking system consists of PID controller and generates velocity command based on the relative distance. The generated velocity command is used as the input of the UAV's original flight controller. The operation of the proposed system was verified through actual flight tests using a marker on top of a moving vehicle and tracks it to successfully demonstrate its capability using a quad-rotor UAV.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1221-1229
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• 2020

In urgent situations such as disasters and accidents, rapid data acquisition and processing is required. Therefore, in this study, a rapid geocoding method according to EOP (Exterior Orientation Parameter) correction was proposed through pattern analysis of the initial UAV image information. As a result, in the research area with a total flight length of 1.3 km and a width of 0.102 ㎢, the generation time of geocoding images took about 5 to 10 seconds per image, showing a position error of about 8.51 m. It is believed that the use of the rapid geocoding method proposed in this study will help provide basic data for on-site monitoring and decision-making in emergency situations such as disasters and accidents.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1067-1076
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• 2020

In this paper, an unsupervised saliency guided change detection method using UAV and aerial imagery is proposed. Regions that are more different from other areas are salient, which make them more distinct. The existence of the substantial difference between two images makes saliency proper for guiding the change detection process. Change Vector Analysis (CVA), which has the capability of extracting of overall magnitude and direction of change from multi-spectral and temporal remote sensing data, is used for generating an initial difference image. Combined with an unsupervised CVA and the saliency, Principal Component Analysis(PCA), which is possible to implemented as the guide for change detection method, is proposed for UAV and aerial images. By implementing the saliency generation on the difference map extracted via the CVA, potentially changed areas obtained, and by thresholding the saliency map, most of the interest areas correctly extracted. Finally, the PCA method is implemented to extract features, and K-means clustering is applied to detect changed and unchanged map on the extracted areas. This proposed method is applied to the image sets over the flooded and typhoon-damaged area and is resulted in 95 percent better than the PCA approach compared with manually extracted ground truth for all the data sets. Finally, we compared our approach with the PCA K-means method to show the effectiveness of the method.