• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1645-1653
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• 2014

In general, RGB, NIR, and thermal images are used for obtaining geospatial data. Such multiband images are collected via devices mounted on satellites or manned flights, but do not always meet users' expectations, due to issues associated with temporal resolution, costs, spatial resolution, and effects of clouds. We believe high-resolution, multiband images can be obtained at desired time points and intervals, by developing a payload suitable for a low-altitude, auto-piloted UAV. To achieve this, this study first established a low-cost, high-resolution multiband image collection system through developing a sensor and a payload, and collected geo-referencing data, as well as RGB, NIR and thermal images by using the system. We were able to obtain a 0.181m horizontal deviation and 0.203m vertical deviation, after analyzing the positional accuracy of points based on ortho mosaic images using the collected RGB images. Since this meets the required level of spatial accuracy that allows production of maps at a scale of 1:1,000~5,000 and also remote sensing over small areas, we successfully validated that the payload was highly utilizable.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.137-143
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• 2013

The high resolution satellite images are used in many fields such as weather observation, remote sensing, military facilities monitoring, cultural properties protection etc. Although satellite images are obtained in same satellite imaging system, the satellite images are degraded depending on the condition of hardware(optical device, satellite operation altitude, image sensor, etc.). Due to the fact that changing the hardware of satellite imaging system is impossible for resolution enhancement of these degraded satellite after launching a satellite, therefore the method of resolution enhancement with satellite images is necessary. In this paper the resolution is enhances by using a Super Resolution(SR) algorithm. The SR algorithm is an algorithm to enhance the resolution of an image by uniting many low resolution images, so an output image has higher resolution than using other interpolation methods. But It is difficult to obtain many images of the same area. Therefore, to solve this problem, we applied SR after by applying the affine and projection transform. As a results, we found that the images applied SR after affine and projection transform have higher resolution than the images only applied SR.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1393-1405
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• 2020

UAV (Unmanned Aerial Vehicle) can acquire high-resolution images due to low-altitude flight, and it can be photographed at any time. Therefore, the UAV images can be updated at any time in map production. Due to these advantages, studies on the possibility of producing large-scale digital maps using UAV images are actively being conducted. Precise digital maps can be used as base data for digital twins or smart cites. For producing a precise digital map, precise sensor modeling using GCPs (Ground Control Points) must be preceded. In this study, geometric models of UAV images were established through a precision sensor modeling algorithm developed in house. Then, a digital map by stereo plotting was produced to evaluate the possibility of large-scale digital map. For this study, images and GCPs were acquired for Ganseok-dong, Incheon and Yeouido, Seoul. As a result of precision sensor modeling accuracy analysis, high accuracy was confirmed within 3 pixels of the average error of the checkpoints and 4 pixels of the RMSE was confirmed for the two study regions. As a result of the mapping accuracy analysis, it satisfied the 1:1,000 mapping accuracy announced by the NGII (National Geographic information Institute). Therefore, the precision sensor modeling technology suggested the possibility of producing a 1:1,000 large-scale digital map by UAV images.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.835-846
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• 2020

Recent severe climate changes and extreme weather events have caused the uncommon types of forest ecosystem disturbances such as hails and gypsy moths. This paper describes the analysis of the forest ecosystem disturbances using ISODATA (Iterative Self-organizing Data Analysis Technique Algorithm) with the RapidEye and Sentinel-2 images, regarding the cases of the hail damages in Hwasun in 2017 and the gypsy moth damages in the Chiak Mountain in 2020. In the case of hail damages, the comparison of the June image of this study and the July field survey of the previous study showed that the damage severity increased from June to July as the drought overlapped after the trees were injured by the hails. In the case of gypsy moths, significant leaf damages were found from the image of June, and the damages were mainly distributed at the low-altitude slope near Wonju City. We made sure that satellite remote sensing is a very effective method to detect various and unusual forest ecosystem disturbances caused by climate change. Also, it is expected that the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024 can be actively utilized to monitor such forest ecosystem disturbances.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.224-231
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• 2020

An optical tracking plays an important role for measurement operation, as it is responsible for low altitude measurements that are difficult to obtain with radar systems. Since the existing optical tracking systems have not been developed in the proving ground itself so far, it is difficult to modify them to fit the environment of the proving ground. Also, they are designed as a vehicle-mounted type, so there is a limitation in selecting an optimal site. The in-house developed small optical tracking system is designed with a simple configuration to overcome these shortcomings and makes it possible for operators to operate the system at any place in the proving ground. In addition, there has been a need of developing small optical trackers by ourselves to be prepared for future research so that artificial intelligence (AI) can be applied to the optical tracking systems. In this paper, we described the design concept of the small optical tracker, the configuration of the components to implement the basic tracking function, and showed the results of the simulation to set the configuration of the equipment according to the characteristics of the flight targets.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1417-1424
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• 2019

Recently, disaster accidents have occurred frequently over the world, and disaster have been continuously studied using remote sensing due to large scale and hard-to-reach features. The collapse of Laos Xe pian-Xe namnoy dam in 2018 also caused a lot of human and economic damage. This study's purpose is to change detect water system due to the collapse of Xe pian-Xe namnoy dam in Laos and to derive areas where future flooding is expected. The water system is extracted from each image of KOMPSAT-5 before and after the dam collapse in order to quantitatively change detect in the water system. The result of the water system area increased more than 10 times after the dam collapse. In addition, it is confirmed that the newly created water system is thickly created in areas of low altitude area. This study result can be used in the future to systematize the pre-response to abnormalities and issues in existing operating dams. And then, if combined with other remote sensing data, more diverse and specific results could be obtained.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.9-13
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• 2022

In this paper, the tracking error of monopulse radar caused by cross-eye jamming using terrain bounce is analyzed. Cross-eye jamming is a method of generating an error in a radar tracking system by simultaneously transmitting two signals with different phases and amplitudes. When the monopulse radar receives the cross-eye jamming signal generated by the terrain bounce, a tracking error occurs in the elevation direction. In the presence of multipath, this signal is a combination of the direct target return and a return seemingly emanating from the target image beneath the terrain surface. Terrain bounce jamming has the advantage of using a single jammer, but the space affecting the jamming is limited by the terrain reflection angle and the degree of scattering of the terrain. This study can be usefully used to protect ships from low-altitude missiles or aircraft in the sea.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.167-175
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• 2019

Water color analysis allows non-destructive estimation of abundance of optically active water constituents in the water body. Recently, there have been increasing needs for light-weighted multispectral cameras that can be integrated with low altitude unmanned platforms such as drones, autonomous vehicles, and heli-kites, for the water color analysis by spectroradiometers. This study performs the preprocessing of the Micasense Rededge-M camera which recently receives a growing attention from the earth observation community for its handiness and applicability for local environment monitoring, and investigates the applicability of Rededge-M data for water color analysis. The Vignette correction and the band alignment were conducted for the radiometric image data from Rededge-M, and the sky, water, and solar radiation essential for the water color analysis, and the resultant remote sensing reflectance were validated with an independent hyperspectral instrument, TriOS RAMSES. The experiment shows that Rededge-M generally satisfies the basic performance criteria for water color analysis, although noticeable differences are observed in the blue (475 nm) and the near-infrared (840 nm) band compared with RAMSES.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.2
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• pp.263-272
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• 1994

The purpose of this study was to identify factors that might distinguish those who have a high level of Intention to purchase each of domestic, foreign designer and national brand jeans from those who have a low intention in terms of evaluative criteria belief, ideal jeans image and clothing altitude. The sample consisted of 198 male and 197 female students from five universities in Seoul. The questionnnaire consisted of 50 seven-point semantic differential scales dealing with evaluative criteria and ideal jeans image, beliefs about and intention to purchase domestic, foreign designer and foreign national brand jeans and 25 Likert type clothing attitude scales. Based on a series of t-tests the results showed that color and design were the most influencing factor among the evaluative criteria belief, regardless of brand type, while durability, accessory, sewing were the least. Sexy image, brand consciousnees and fashion interest were the important factor that distinguish high intention to purchase group fro)m low intention to purchase group.