• Korean Journal of Heritage: History & Science
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• v.46 no.3
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• pp.78-93
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• 2013

The purpose of this study is to analyze college students' perception of national natural heritages, including natural monumentsand scenic sites, in comparison with the similar concepts of national parks and eco-landscape preservation areas, to suggest managerial implications to enhance competitiveness. The first objective of this study is to measure their attitude toward traveling each type of natural heritage and to rate the relative importance of the four types of heritages in terms of preservation. Natural monuments were perceived as the most strongly preserved type, while scenic sites were perceived as the least strongly preserved type. The second objective is to conduct a correspondence analysis to match the concepts of four types of natural heritages with 10 tourist attractions representing the types. It was found that college students have difficulty appropriately identifying the types of 10 tourist attractions. In addition, multi-dimensional scaling (MDS) was implemented to identify the similarities and differences of the four types of natural heritages and to produce a positioning map matching the four types of natural heritages with the six attributes representing each type as a tourist attraction. Natural monuments were perceived very differently from scenic sites and not very differently from eco-landscape preservation areas. There were a few associations between the four types of natural heritages and the six tourism attributes, implying that little effort is made to promote and position each type of natural heritage in terms of tourism. In conclusion, a public awareness program is required to enhance the brand image of natural monuments and scenic sites in comparison to national parks and eco-landscape preservation areas. In addition, local residents who live near the natural heritages should be bolstered to play a managerial role as supporters and contents providers for sustainability.

• Journal of Korea Water Resources Association
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• v.52 no.4
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• pp.279-289
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• 2019

Unlike other natural disasters, drought is a reoccurring and region-wide phenomenon after being triggered by a prolonged precipitation deficiency. Considering that remote sensing products provide consistent temporal and spatial measurements of precipitation, this study developed a remote sensing data-based drought outlook model. The meteorological drought was defined by the Standardized Precipitation Index (SPI) achieved from PERSIANN_CDR, TRMM 3B42 and GPM IMERG images. Bayesian networks were employed in this study to combine the historical drought information and dynamical prediction products in advance of drought outlook. Drought outlook was determined through a decision-making model considering the current drought condition and forecasted condition from the Bayesian networks. Drought outlook condition was classified by four states such as no drought, drought occurrence, drought persistence, and drought removal. The receiver operating characteristics (ROC) curve analysis were employed to measure the relative outlook performance with the dynamical prediction production, Multi-Model Ensemble (MME). The ROC analysis indicated that the proposed outlook model showed better performance than the MME, especially for drought occurrence and persistence of 2- and 3-month outlook.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.10-15
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• 2020

Ultraviolet rays, which have wavelengths smaller than 400 nm, are very harmful to the eyes. Recently, high-energy visible light was also revealed to be harmful to retinal cells. Therefore, polymer eyeglass lenses that can block UV and high-energy visible light are needed for eye health. In this study, high-refractive-index polymer eyeglass lens, n=1.67, were manufactured using the injection-mold method with the m-xylene diisocyanate monomer, 2,3-bis((2-mercaptoethyl)thio)-1-propanethiol monomer, benzotriazole UV absorber, release of alkyl phosphoric ester, dye mixture of CI solvent violet 13, and catalyst of dibutyltin dichloride mixture. A multi-layer anti-reflection coating was applied to manufactured polymer eyeglass lenses for both sides using an E-beam evaporation system. The optical properties of the manufactured lenses with the UV and high-energy visible light-blocking function were analyzed by UV-visible spectrophotometry. As a result, the polymer eyeglass lens with a UV absorber of 0.5 wt. % blocked 99% of UV and high-energy visible light shorter than 411 nm. The average transmittance of the polymer eyeglass lens with a UV absorber of 0.5wt.% was 97.9% in the range of 460 ~ 660 nm for photopic eye sensitivity higher than 10%. Therefore, clear image acquisition in photopic vision is possible.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.318-329
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• 2022

Plant phenology including flowering, leaf unfolding, and leaf coloring in a forest is important to understand the forest ecosystem. Temperature rise due to recent climate change, however, can lead to plant phenology change as well as snowfall in winter season. Therefore, accurate monitoring of forest environment changes such as plant phenology and snow cover is essential to understand the climate change effect on forest management. These changes can monitor using a digital camera system. This paper introduces the detection methods for plant phenology and snow cover at the mountain region using an unmanned camera system that is a way to monitor the change of forest environment. In this study, the Automatic Mountain Meteorology Stations (AMOS) operated by Korea Forest Service (KFS) were selected as the testbed sites in order to systematize the plant phenology and snow cover detection in complex mountain areas. Multi-directional Internet Protocol (IP) camera system that is a kind of unmanned camera was installed at AMOS located in Seoul, Pyeongchang, Geochang, and Uljin. To detect the forest plant phenology and snow cover, the Red-Green-Blue (RGB) analysis based on the IP camera imagery was developed. The results produced by using image analysis captured from IP camera showed good performance in comparison with in-situ data. This result indicates that the utilization technique of IP camera system can capture the forest environment effectively and can be applied to various forest fields such as secure safety, forest ecosystem and disaster management, forestry, etc.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.11-20
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• 2022

The main purpose of this study is to investigate the applicability of the shear wave tomography technology as a non-destructive testing method to evaluate the debonding between the track concrete layer (TCL) and the hydraulically stabilized based course (HSB) of concrete slab tracks for the Korea high-speed railway system. A commercially available multi-channel shear wave measurement device (MIRA) is used to evaluate debonding defects in full-scaled mock-up test specimen that was designed and constructed according to the Rheda 200 system. A part of the mock-up specimen includes two artificial debonding defects with a length and a width of 400mm and thicknesses of 5mm and 10mm, respectively. The tomography images obtained by a MIRA on the surface of the concrete specimens are effective for visualizing the debonding defects in concrete. In this study, a simple image processing method is proposed to suppress the noisy signals reflected from the embedded items (reinforcing steel, precast sleeper, insert, etc.) in TCL, which significantly improves the readability of debonding defects in shear wave tomography images. Results show that debonding maps constructed in this study are effective for visualizing the spatial distribution and the depths of the debondiing defects in the railway concrete slab specimen.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.2
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• pp.130-137
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• 2023

This study analyzed the effect of mixing order on the flowability, compressive strength, and flexural strength of cement composites reinforced with polyvinyl alcohol(PVA) fibers and multi-walled carbon nanotubes(MWCNTs). The experimental results showed that the addition of CNTs significantly reduced the flowability, and the flowability was considerably affected by the mixing order when CNTs were added. The compressive strength was most effectively improved when water and CNTs solution were mixed first before adding PVA fibers, and the flexural strength was highest when water and CNTs solution were mixed with PVA fibers after dry mixing. However, there was no clear correlation between the flexural toughness and the mixing order. In addition, scanning electron microscopy(SEM) image analysis was conducted to analyze the microstructure. The SEM images showed that CNTs were randomly dispersed through the specimens and contributed to the strength improvement, but the effect of the mixing order was not clearly observed. The main results of this study are expected to be useful for evaluations of workability and material performance of PVA fiber-reinforced cement composites with CNTs.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.1-19
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• 2020

A river bed which is submerged in water at high flow and becomes part of the river at low flow, serves as a bridge between the river and the land. The channel bar creates a unique ecosystem with vegetation adapted to the particular environment and the water pool forms a wetland that plays a very important role in the environment. To evaluate anthropogenic impacts on the river bed in the Middle Yeongsangang River, the fluvial landforms in the stream channel were analyzed using multi-temporal remotely-sensed images. In the aerial photograph of 2005 taken before the construction of the large weirs, oxbow lakes, mid-channel bars, point bars, and natural wetlands between the artificial levees were identified. Multiple bars divided the flow of stream water to cause the braided pattern in a particular section. After the construction of the Seungchon weir, aerial photographs of 2013 and 2015 revealed that most of the fluvial landforms disappeared due to the dredging of its riverbed and water level control(maintenance at 7.5El.m). Sentinel-2 images were analyzed to identify differences between before and after the opening of weir gate. Change detection was performed with the near infrared and shortwave infrared spectral bands to effectively distinguish water surfaces from land. As a result, water surface area of the main stream of the Yeongsangang River decreased by 40% from 1.144km² to 0.692km². A large mid-channel bar that has been deposited upstream of the weir was exposed during low water levels, which shows the obvious influence of weir on the river bed. Newly formed unvegetated point bars that were deposited on the inside of a meander bend were identified from the remotely sensed images. As the maintenance period of the weir gate opening was extended, various habitats were created by creating pools and riffles around the channel bars. Considering the ecological and hydrological functions of the river bed, it is expected that the increase in bar areas through weir gate opening will reduce the artificial interference effect of the weir.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1679-1692
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• 2023

South Korea is a country that emits a large amount of pollutants as a result of population growth and industrial development and is also severely affected by transboundary air pollution due to its geographical location. As pollutants from both domestic and foreign sources contribute to air pollution in Korea, the location of air pollutant emission sources is crucial for understanding the movement and distribution of pollutants in the atmosphere and establishing national-level air pollution management and response strategies. Based on this background, this study aims to effectively acquire spatial information on domestic and international air pollutant emission sources, which is essential for analyzing air pollution status, by utilizing high-resolution optical satellite images and deep learning-based image segmentation models. In particular, industrial parks and quarries, which have been evaluated as contributing significantly to transboundary air pollution, were selected as the main research subjects, and images of these areas from multi-purpose satellites 3 and 3A were collected, preprocessed, and converted into input and label data for model training. As a result of training the U-Net model using this data, the overall accuracy of 0.8484 and mean Intersection over Union (mIoU) of 0.6490 were achieved, and the predicted maps showed significant results in extracting object boundaries more accurately than the label data created by course annotations.