• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.555-562
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• 2021

Recently, in the field of geospatial information construction, unmanned aerial vehicles have been increasingly used because they enable rapid data acquisition and utilization. In this study, photogrammetry was performed using fixed-wing, rotary-wing, and VTOL (Vertical Take-Off and Landing) unmanned aerial vehicles, and geospatial information was constructed using two types of unmanned aerial vehicle LiDAR (Light Detection And Ranging) sensors. In addition, the accuracy was evaluated to present the utility of spatial information constructed through unmanned aerial photogrammetry and LiDAR. As a result of the accuracy evaluation, the orthographic image constructed through unmanned aerial photogrammetry showed accuracy within 2 cm. Considering that the GSD (Ground Sample Distance) of the constructed orthographic image is about 2 cm, the accuracy of the unmanned aerial photogrammetry results is judged to be within the GSD. The spatial information constructed through the unmanned aerial vehicle LiDAR showed accuracy within 6 cm in the height direction, and data on the ground was obtained in the vegetation area. DEM (Digital Elevation Model) using LiDAR data will be able to be used in various ways, such as construction work, urban planning, disaster prevention, and topographic analysis.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.105-116
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• 2023

As forest fires' scale has increased, they have become disasters that destroy not only forests but also property, human psychological balance, and even human lives. As a result, governmental support has become a crucial part of the forest fire restoration process. Quickly restoring victims' quality of life (QOL) from not only an ecological perspective but also from their human perspective has become an important goal. Therefore, through structural equation modeling, this study analyzed effects of government support, post-traumatic stress disorder (PTSD), and resilience on 195 Uljin and Samcheok forest fire victims' QOL. In the final research model, the total standardized effect on QOL of government support to PTSD and resilience was found to have significant effect (0.417). By path, the effect of government support on QOL through resilience was verified as 0.172. Examination of the path between latent variables revealed that resilience had the greatest influence on QOL, and government support had a significant effect, thus confirming that they were the main factors affecting QOL.

• Journal of the Korean Geotechnical Society
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• v.26 no.11
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• pp.89-98
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• 2010

A method to design a critical height of embankments is presented so as to mobilize fully soil arching in pile-supported embankments. The behavior of the load transfer of embankment weights on pile cap beams was investigated by a series of model tests performed on pile-supported embankments with relatively wide space between cap beams. The model tests explained that the behavior of the load transfer depended very much on the height of embankments, because soil arching could be mobilized in pile-supported embankments only under enough high embankments. The measured vertical loads on cap beams coincided with the predicted ones estimated by the theoretical equations, which have been presented in the previous studies on the basis of load transfer mechanisms according to either the punching shear failure mode during low filling stage or the soil arching failure mode during high filling stage. The mechanism of the load transfer was shifted beyond a critical height of embankment from the punching shear mechanism to the soil arching mechanism. Therefore, in order to mobilize soil arching in pile-supported embankments, the embankments should be designed at least higher than the critical height. A theoretical equation to estimate the critical height could be derived by equalizing the vertical loads estimated by the load transfer mechanisms on the basis of both the punching shear and the soil arching. The derived theoretical equation could predict very well the experimental critical height of embankment.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.201-209
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• 2022

In order for the military to review the introduction of virtual reality technology into various education and training systems and fully utilize it, it is important to reflect the characteristics of the technology and education system and to accurately identify and selectively apply the characteristics of commercialization. In this study, the evaluation criteria were selected through the Analitic Hierarchy Process (AHP) method for factors to be considered when commercializing a virtual reality-based education and training system, and the priorities of the projects were determined. Based on previous studies, an initial AHP model was constructed and the relative importance of six factors, including reality, was analyzed as the level 1 evaluation criteria. Next, for Level 2, each evaluation criterion was evaluated to confirm the importance of each of the 11 tasks in the six evaluation criteria, and priorities were selected for each task. As a result of the analysis, level 1 showed that reality and ripple had higher importance than other factors. As a result of evaluating the final relative importance, the priority was shown in the order of ① flight training, ② disaster training, ③ shooting Training, and ④ driving a vehicle. Based on the relative priorities determined in Levels 1 and 2 of the model presented in this study, the importance of each project necessary for final decision-making of the research priorities for the defense virtual reality project was presented. It is expected that this study can be used as a reference material for prioritizing the commercialization of education and training systems in the defense sector.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.501-509
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• 2006

The safety of levee that depends on the river flood elevation has been regarded as very important keys to build up various flood prevention systems. However, deterministic methods for computation of water surface profile cannot reflect the effect of possible inaccuracies in the input parameters. The purpose of this study is to develop a methodology of uncertainty computation of design flood level based on steady flow analysis and Monte Carlo simulation. This study addresses the uncertainty of water surface elevation by Manning's coefficients, design discharges, river cross sections and boundary condition. Monte Carlo simulation with the variations of these parameters is performed to quantify the variations of water surface elevations in a river. The proposed model has been applied to the Kumho-river. The reliability analysis was performed within 38.5 km (95 sections) reach considered the variations of the above-mentioned parameters. Overtopping risks were evaluated by comparing the elevations of the flood condition with the those of the levees. The results show that there is a necessity which will raise the levee elevation between 1 cm and 56 cm at 7 sections. The model can be used for preparing flood risk maps, flood forecasting systems and establishing flood disaster mitigation plans as well as complement of conventional levee design.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1371-1388
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• 2023

Floods are becoming more severe and frequent due to global warming-induced climate change. Water disasters are rising in Korea due to severe rainfall and wet seasons. This makes preventive climate change measures and efficient water catastrophe responses crucial, and synthetic aperture radar satellite imagery can help. This research created 1,423 water body learning datasets for individual water body regions along the Han and Nakdong waterways to reflect domestic water body properties discovered by Sentinel-1 satellite radar imagery. We created a document with exact data annotation criteria for many situations. After the dataset was processed, U-Net, a deep learning model, analyzed water body detection results. The results from applying the learned model to water body locations not involved in the learning process were studied to validate soil water body monitoring on a national scale. The analysis showed that the created water body area detected water bodies accurately (F1-Score: 0.987, Intersection over Union [IoU]: 0.955). Other domestic water body regions not used for training and evaluation showed similar accuracy (F1-Score: 0.941, IoU: 0.89). Both outcomes showed that the computer accurately spotted water bodies in most areas, however tiny streams and gloomy areas had problems. This work should improve water resource change and disaster damage surveillance. Future studies will likely include more water body attribute datasets. Such databases could help manage and monitor water bodies nationwide and shed light on misclassified regions.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.859-873
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• 2023

Wildfires cause a lot of environmental and economic damage to the Earth over time. Various experiments have examined the harmful effects of wildfires. Also, studies for detecting wildfires and pollutant emissions using satellite remote sensing have been conducted for many years. The wildfire product for the Geostationary Environmental Monitoring Spectrometer (GEMS), Korea's first environmental satellite sensor, has not been provided yet. In this study, a false-color composite for better expression of wildfire smoke was created from GEMS and used in a U-Net model for wildfire detection. Then, a classification model was constructed to distinguish yellow dust from the wildfire smoke candidate pixels. The proposed method can contribute to disaster monitoring using GEMS images.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.543-551
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• 2023

As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.169-178
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• 2024

While stable mid- to large-scale underground hydrogen storage infrastructures are needed to meet the rapidly increasing demand for hydrogen energy, evaluating the safety of explosion vibrations in adjacent buildings is becoming important because of gas explosions in underground hydrogen storage facilities. In this study, a numerical analysis of vibration safety effects on nearby building structures was performed assuming a hydrogen gas explosion disaster scenario in a low-depth underground hydrogen storage facility. A parametric study using a meta-model was conducted to predict changes in ground dynamic behavior for each combination of ground properties and to analyze sensitivity to geotechnical influencing factors. Directly above the hydrogen storage facility, the unit weight of the ground had the greatest influence on the change in ground vibration due to the explosion, whereas, farther away from the facility, the sensitivity of dynamic properties was found to be high. In addition, in evaluating the vibration stability of ground building structures based on the predicted ground vibration data and blasting vibration tolerance criteria, in the case of large reinforced concrete building structures, the ground vibration safety was guaranteed with a separation distance of about 10-30 m.