• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.471-478
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• 2020

In this paper, we develop the ground risk model of unmanned aerial vehicle (UAV) operation to quantify the ground risk when the UAV falls to the ground during the intended operation in case of UAV failure. The ground risk is computed by using the UAV failure probability, the probability of impact a person when UAV falls to the ground, the probability of fatality when UAV strikes the person. We mathematically derive each probability to evaluate the ground risk of UAV operation. Also, the population density map, building to land ratio map, car traffic database is used to estimate the number of people exposed to collision with UAV. Finally, we assumed the operations of a UAV with two paths in Daejeon city and evaluate the ground risk of each UAV operations.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.334-343
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• 2023

Purpose: In this study, the cavity data found through ground cavity exploration was combined with underground facilities to derive a correlation, and the ground subsidence prediction map was verified based on the AI algorithm. Method: The study was conducted in three stages. The stage of data investigation and big data collection related to risk assessment. Data pre-processing steps for AI analysis. And it is the step of verifying the ground subsidence risk prediction map using the AI algorithm. Result: By analyzing the ground subsidence risk prediction map prepared, it was possible to confirm the distribution of risk grades in three stages of emergency, priority, and general for Busanjin-gu and Saha-gu. In addition, by arranging the predicted ground subsidence risk ratings for each section of the road route, it was confirmed that 3 out of 61 sections in Busanjin-gu and 7 out of 68 sections in Sahagu included roads with emergency ratings. Conclusion: Based on the verified ground subsidence risk prediction map, it is possible to provide citizens with a safe road environment by setting the exploration section according to the risk level and conducting investigation.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.5-10
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• 2022

Ground Subsidence has been continuously occurring in densely populated downtown. The main cause of ground subsidence is the damaged underground facility like sewer. Currently, ground subsidence is being dealt with by discovering cavities in ground using GPR. However, this consumes large amount of manpower and cost, so it is necessary to predict hazardous area for efficient operation of GPR. In this study, ◯◯city is divided into 500 m×500 m grids. Then, data set was constructed using the characteristics of the underground facility and ground subsidence in grids. Data set used to machine learning model for ground subsidence risk grade prediction. The purposed model would be used to present a ground subsidence risk map of target area.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.6 s.40
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• pp.31-43
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• 2004

Seismic risk assessment of bridge is presented using fragility curves which represent the probability of damage of a structure virsus the peak ground acceleration. In theseismic fragility analysis, the structural damage is defined using the rotational ductility at the base of the bridge pier, which is obtained through nonlinear dynamic analysis for various input earthquakes. For the assessment of seismic risk of bridge, peak ground accelerations are obatined for various return periods from the seismic hazard map of Korea, which enables to calculate the probability density function of peak ground acceleration. Combining the probability density function of peak ground acceleration and the seismic fragility analysis, seismic risk assessment is performed. In this study, seismic fragility analysis is developed as a function of not the surface motion which the bridge actually suffers, but the rock outcrop motion which the aseismic design code is defined on, so that further analysis for the seismic hazard assessment may become available. Besides, the effects of the friction pot bearings and the friction pendulum bearings on the seismic fragility and risk analysis are examined. Lastly, three regions in Korea are considered and compared in the seismic risk assessment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.10-17
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• 2020

Recently, the liquefaction phenomenon was first discovered in Korea due to a magnitude 5.4 earthquake that occurred in Pohang, Gyeonsangbuk-do. When liquefaction occurs, some of the water and sand are ejected to the ground, producing a space, which leads to various dangerous situations, such as ground subsidence, building collapse, and sinkhole generation. Recently, the necessity of producing a liquefaction risk map in Korea has increased to grasp potential liquefaction areas in advance. Therefore, this study examined the drilling information from the national geotechnical information DB center at the Ministry of Land, Infrastructure, and Transport to produce a liquefaction risk map, and developed a module to implement functions for basic data modeling and 3D analysis based on drilling information database extraction and information. Through this study, effective interlocking technology of the integrated database of national land information was obtained, and three-dimensional information was generated for each stage of liquefaction risk analysis, such as soil resistance value and a liquefaction risk map. In the future, the technology developed in this study can be used as a comprehensive decision support technology for establishing a foundation for building 3D liquefaction information and for establishing a response system of liquefaction.

• Journal of the Korean Geotechnical Society
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• v.38 no.9
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• pp.69-77
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• 2022

Several studies have been conducted to analyze the risk of ground subsidence occurring in urban areas. Recently, the correlation between the density of underground utilities (i.e., the quantity of buried utilities in the analysis area) and the recorded ground subsidence has been explored to analyze such risk through. Choi et al. (2021) proposed an algorithm to optimize the correlation between the ground subsidence and normalized linear density of underground pipelines. In this study, the optimization algorithm was modified for analysis based on the risk grade. The analysis results using the modified optimization algorithm were compared with the correlation analysis results between the density of underground utilities and recorded ground subsidence presented by Choi et al. (2021). Compared with Choi et al. (2021), three analysis results showed equal or higher accuracy in the correlation analysis with recorded ground subsidence according to risk grade. In particular, for R100, it was divided into five grades and compared with the ratio of the recorded ground subsidence that occurred in grades 4 or higher. As a result, Choi et al. (2021) showed that 86% of recorded ground subsidence occurred in grades 4 or higher, whereas this study showed 93%. It was confirmed that the accuracy of the modified optimization algorithm was improved. The modified optimization algorithm can be applied to develop a ground subsidence risk map for each grade in an urban area, which can be used as basic data for decision-making for underground utility maintenance.

• 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.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.893-903
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• 2008

A method for predicting surface failures which occur during heavy rainfall on mountain slopes is proposed by using the digital land form model that is obtained by reading altitude on a topographical map at 10m grid point space. A depth of a potential failure layer is assumed at each grid point. In the layer, an infiltrated water movement from cell to cell is modeled in the study (cell is a square of the grid). Infiltrated ground water levels which show the three dimensional effects of a topographical factor in an area can be hourly calculated at every cell by the model. The safety factor of every cell is also calculated every hour by the infinite slope stability analysis method with the obtained infiltrated ground water level. Failure potential delineation is defined here as the time when the safety factor becomes less than unity under the assumptions that effective rainfall is 20mm/h and continues 20 hours.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.95-101
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• 2021

In this study, we present how to improve the current seismic disaster information service by utilizing Shake, which can express the effects of earthquakes in the form of isolines. Using ShakeMap software provided by the U.S. Geological Survey, an automated rapid ShakeMap generation system was implemented, and based on this, an earthquake disaster information service improvement model was presented to identify earthquake risk in the form of intensity or peak ground acceleration. In order to verify the feasibility and effectiveness of the improved model, the seismic disaster information service app. was developed and operated on a trial basis in Pohang, Gyeongsangbuk-do. As a result of the operation, it was found that more detailed seismic risk information could be provided by providing information using rapid ShakeMap to induce users' safety behavior more effectively.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.3
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• pp.237-243
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• 2007

Probabilistic seismic risk analysis was performed. Exceeding probabilities of combined stress and maximum horizontal displacement of steel piled pier due to surface ground motion which was transferred from base rock motion was expressed as seismic fragility curves. Occurrence probability of peak ground motion was calculated by using the seismic hazard map on design code for harbor and fishery structures of Korea. Finally seismic risk of pier structure was found by combining the fragility and the hazard and those were presented through numerical analysis.