• Journal of Korean Society of Disaster and Security
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• v.14 no.1
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• pp.41-50
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• 2021

As a method of predicting the displacement of river levee in advance, Differential Interferometry (D-InSAR) kind of InSAR techniques was used to identify weak points in the area of the levee collapes near Gumgok Bridge (Somjin River) in Namwon City, which occurred in the summer of 2020. As a result of analyzing the displacement using five images each in the spring and summer of 2020, the Variation Index (V) of area where the collapse occurred was larger than that of the other areas, so the prognostic sysmptoms was detected. If the levee monitoring system is realized by analyzing the correlations with displacement results and hydrometeorological factors, it will overcome the existing limitations of system and advance ultra-precise, automated river levee maintenance technology and improve national disaster management.

• Korean Journal of Environment and Ecology
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• v.22 no.2
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• pp.119-127
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• 2008

This research managed to establish the space information on incidence factors of landslide targeting Bukhansan National Park and aimed at suggesting a basic data for disaster prevention of a landslide for the period to come in Bukhansan National Park through drawing up the map indicating vulnerability to a landslide and ecological risks by the use of overlay analysis and adding-up estimation matrix analysis methods. This research selected slope angle, slope aspect, slope length, drainage, vegetation index(NDVI) and land use as an assessment factor of a landslide and constructed the spatial database at a level of '$30m\times30m$' resolution. The analysis result was that there existed high vulnerability to a landslide almost all over Uidong and Dobong valleys. As for ecological risks, Dobong valley, Yongueocheon valley, Jeongneung valley and Pyeongchang valley were analyzed to be higher, so it is judged that the impact on a landslide risk should be also considered in time of establishing a management plan for these districts for the time to come.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.37-46
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• 2020

Although the importance of resilience is emerging around the world, the single definition of resilience related to natural disasters is not clear. The reason for this is that there is no specific definition of how the definition of resilience relates to similar terms such as vulnerability, recovery, adaptability, and sustainability. In addition, it is because each country and region have different geographic and geological characteristics, and each measurement index is different, just as typhoons, droughts, and earthquakes have different types of disasters. Therefore, in this study, the definition of resilience is reflected in the spatial characteristics of this study as the ability to recover from'complex disasters (concentrated heavy rain, landslides, earth and stone flows) occurring on local roads or on local roads adjacent to people or facilities. Defined. And it was divided into DRR: Disaster Resilience focusing on the Road. In addition, domestic and foreign literature surveys were conducted to derive road-centered disaster resilience factors, and a hierarchical structure was established and AHP survey was conducted to establish a DRR evaluation system. As a result of the analysis of the AHP survey, the weight of direct road disaster influencing factors (drainage facilities, protection facilities, etc.) located inside local roads was 0.742, and the weight of indirect road disaster influencing factors (population, property, etc.) located near local roads. Was found to be 0.258, indicating that the direct impact factor of road disaster was relatively higher than that of the indirect impact factor.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.149-149
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• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.6
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• pp.235-241
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• 2018

In this study, we collected cases of accidents caused by swell in the east coast of Korea from 2013 to 2017. The location of the accident, the season, the type of coast and the type of damage were classified and the correlation between the accident and the wave data was analyzed by collecting the observation data of the nearby area at the time of the accident. Also, based on the results of the coastal disaster vulnerability assessment of Korea Hydrographic and Oceanographic Agency, the vulnerability grades of swell accidents area were evaluated. In swell accident area, the average grade of the wave exposure index was 4.91, the wave sensitivity index was 3.87, and the wave impact index was 4.90. As a result, most of the swell accidents occurred in the 5 grade (very vulnerable level) of the wave impact index, and the area of the east coast (78.7%) of the same 5 grade was classified into five types according to the wave sensitivity index result. Finally, a countermeasures was taken for characteristics of each type.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.65-80
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• 2020

This paper deals with risk assessment of life in a landslide-prone area by a GIS-based modeling method. Landslide susceptibility maps can provide a probability of landslide prone areas to mitigate or proper control this problems and to take any development plan and disaster management. A landslide inventory map of the study area was prepared based on past historical information and aerial photography analysis. A total of 550 landslides have been counted at the whole study area. The extracted landslides were randomly selected and divided into two different groups, 50% of the landslides were used for model calibration and the other were used for validation purpose. Eleven causative factors (continuous and thematic) such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in hazard analysis. The correlation between landslides and these factors, pixels were divided into several classes and frequency ratio was also extracted. Eventually, a landslide susceptibility map was constructed using a logistic regression model based on entire events. Moreover, the landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract a success rate curve. Based on the results, logistic regression produced an 85.18% accuracy, so we believed that the model was reliable and acceptable for the landslide susceptibility analysis on the study area. In addition, for risk assessment, vulnerability scale were added for social thematic data layer. The study area predictive landslide affected pixels 2,000 and 5,000 were also calculated for making a probability table. In final calculation, the 2,000 predictive landslide affected pixels were assumed to run. The total population causalities were estimated as 7.75 person that was relatively close to the actual number published in Korean Annual Disaster Report, 2006.

• Spatial Information Research
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• v.22 no.4
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• pp.77-87
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• 2014

Recently there are many disasters caused by volcanic activities such as the eruptions in Tungurahua, Ecuador(2014) and $Eyjafjallaj\ddot{o}kull$, Iceland(2010). Therefore, it is required to prepare countermeasures for the disasters. This study analyzes the Baekdu Mountain area, where is the risky area because it is active volcano, based on the observed data and scientific methods in order to assess a risk, produce a hazard map and analyze a degree of risk caused by the volcano. Firstly, it is reviewed for the research about the Baekdu mountain volcanic eruption in 1215(${\pm}15$ years) done by Liu Ruoxin. And the factors causing volcanic disaster, environmental effects, and vulnerability of Baekdu Mountain are assessed by the dataset, which includes the earthquake monitoring data, the volcanic deformation monitoring data, the volcanic fluid geochemical monitoring data, and the socio-economic statistics data. A hazard, especially caused by a volcano, distribution map for the Baekdu Mountain Area is produced by using the assessment results, and the map is used to establish the disaster risk index system which has the four phases. The first and second phases are very high risky area when the Baekdu Mountain erupts, and the third and fourth phases are less dangerous area. The map shows that the center of mountain has the first phase and the farther area from the center has the lower phase. Also, the western of Baekdu Mountain is more vulnerable to get the risk than the eastern when the factors causing volcanic disasters are equally applied. It seems to be caused by the lower stability of the environment and the higher vulnerability.

• Journal of Environmental Policy
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• v.5 no.4
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• pp.1-18
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• 2006

Recently, the damage by fresh flood increases in Gangwon-do and Gyeongsangbuk-do of the north-eastern area of Korea. Even though the recent pattern of rain fall keeps changing, there is no strategy to mitigate damage by disaster. For the appropriate measure and policy for decreasing damage, an index for vulnerability is necessary to provide evidence of local climate change. The present work analyzes the flooding damage cost during the past 20 years. During 80's, the southern area of Korea was seriously damaged by over-floods on the agricultural ground. After that time, the loss and damage has decreased in the southern area but the middle part has shown slight but distinct increases of damage. The absolute coast of damage in the northern part has kept constant. However, the relative regional damage to the total country damage has kept increasing over 20 years in the same area. The surface area of floods is strongly correlated with the regional damage cost in the southern part but the north-eastern part has weak correlation between flooded area and cost. It implies that the recent damage in the north-eastern mountain area was not caused by flood itself but the other factors such as avalanches. The present work expects that the damage cost can be a good proxy value for index for climate change impact assessment.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.25-25
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• 2015

본 논문의 목적은 전 세계적으로 기후변화로 인한 이상기후에 대한 관심이 높아지고 있으며 이로 인한 부정적 영향에 대한 우려가 증가되고 있다. 우리나라도 기후변화로 연평균 강수량이 1910년대 1,155mm에서 2000년대 1,375mm로 약 19% 증가했으며 21세기말에는 약 17%가 증가할 것으로 전망하고 있다. 정부간협의체(Intergovernmental Panel on Climate Change, IPCC)에 따르면 미래에는 지구의 연평균기온은 2050년은 $2.3^{\circ}C$ 2100년엔 $4.8^{\circ}C$가 증가할 것이라고 전망하였고, 우리나라의 경우 2050년에 $3.2^{\circ}C$ 2100년에 $6^{\circ}C$가 증가할 것으로 전망하였다. 따라서 본 연구에서는 최근 지구적인 문제로 대두되어 온 기후변화 대해 재해취약성 분석을 통하여 효과적인 대응방안을 모색하고자 하였다. 연구대상의 지역은 강원도의 18개 시, 군 지자체로 하였으며 계산의 평가단위는 각 지자체를 하나의 집계구로 정하였다. 재해취약성 분석 지표로는 현재(2000년)와 미래(2020년, 2050년)로 나누어서 분석하였다. 분석 결과 2000년에는 영동지역과 원주시가 가장 취약하였으며, 2020년에는 속초와 강릉, 춘천시가, 2050년에는 강원도 중부지역이 가장 취약할 것으로 전망되었다.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.