• Journal of the Korean Geotechnical Society
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• 제33권10호
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• pp.5-14
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• 2017

The hazard maps for predicting collapse on natural slopes consist of a combination of topographic, hydrological, and geological factors. Topographic factors are extracted from DEM, including aspect, slope, curvature, and topographic index. Hydrological factors, such as soil drainage, stream-power index, and wetness index are most important factors for slope instability. However, most of the urban areas are located on the plains and it is difficult to apply the hazard map using the topography and hydrological factors. In order to evaluate the risk of subsidence of flat and low slope areas, soil depth and groundwater level data were collected and used as a factor for interpretation. In addition, the reliability of the hazard map was compared with the disaster history of the study area (Gangnam-gu and Yeouido district). In the disaster map of the disaster prevention agency, the urban area was mostly classified as the stable area and did not reflect the collapse history. Soil depth, drainage conditions and groundwater level obtained from boreholes were added as input data of hazard map, and disaster vulnerability increased at the location where the actual subsidence points. In the study area where damage occurred, the moderate and low grades of the vulnerability of previous hazard map were 12% and 88%, respectively. While, the improved map showed 2% high grade, moderate grade 29%, low grade 66% and very low grade 2%. These results were similar to actual damage.

• The Journal of Engineering Geology
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• 제30권4호
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• pp.663-671
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• 2020

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.

• Water for future
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• 제47권7호
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• pp.86-91
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• 2014

• Journal of Korean Society for Geospatial Information Science
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• 제16권4호
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• pp.33-39
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• 2008

Typhoon Lusa in 2002 and Typhoon Maemi in 2003 caused the worst damage of landslide and debris flow to Gangwon-do. This damage includes severe damage in riverside road. The damage register indicates that this damage is concentrated on mountain areas in Gangwon-do. In recent years, the studies on GIS application to predicting landslide and debris flow have been progressing actively. Landslide risk map managed by The Forest Service is the representative one. In this study, we generated landslide and debris flow hazard maps using statistical analysis and deterministic analysis in Gangnung area where Typhoons caused severe damage to riverside roads. We built damage point GIS DB from damage registers of National Road Maintenance Agency and field survey, and verified accuracy of landslide and debris flow hazard maps using GIS methods.

• Journal of the Korean GEO-environmental Society
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• 제18권6호
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• pp.21-30
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• 2017

This study analyzed the ground characteristics region by designating 3 research areas, Anrim-dong in Chungju City, Busa-dong in Daejeon Metropolitan City and Sinan-dong in Andong City out of the areas subject to concentrated management to prepare for sediment disaster in downtown areas. The correlation between ground characteristics were observed by using characteristics (crown density, root cohesion, rainfall characteristics, soil characteristics) and the risk areas were predicted through sediment disaster prediction modeling. Landslide MAPping (LSMAP), Stability Index MAPping (SINMAP) and Landslide Hazard MAP (LHMAP) were used for the comparative analysis of the hazard prediction model for sediment disaster. As a result of predicting the sediment disaster danger, in case of SINMAP which was generally used, excessive range was predicted as a hazardous area and in case of the Korea Forest Service's landslide hazard map (LHMAP), the smallest prediction area was assessed. LSMAP predicted a medium range of SINMAP and LHMAP as hazardous area. The difference of the prediction results is that the analysis parameters of LSMAP is more diverse and engineering than two comparative models, and it is found that more precise prediction is possible.

• Korean Journal of Remote Sensing
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• 제36권2_1호
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• pp.217-229
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• 2020

Recently, weather changes in Korea have intensified due to global warming, and the five major natural disasters that occur mostly include heavy rains, typhoons, storms, heavy snow, and earthquakes. Busan is vulnerable to snow disaster, given that the amount of natural disaster damage in Busan accounts for more than 50% of the total amount in the entire metropolitan cities in Korea, and that the Busan area includes many hilly mountains. In this study, we attempted to identify vulnerable areas for snowfall disasters in Busan areas using the geographic information system (GIS) with the data for both geographical and anthropogenic characteristics. We produced the maps of vulnerable areas for evaluating factors that include altitude, slope, land cover, road networks, and demographics, and overlapped those maps to rank the vulnerability to snowfall disasters as the 5th levels finally. To weight each evaluating factor, we used an entropy method. The riskiest areas are characterized by being located in mountainous areas with roads, including Sansung-ro in Geumjeong-gu, Mandeok tunnel in Buk-gu, Hwangnyeongsan-ro in Suyeong-gu, and others, where road restrictions were actually enforced due to snowfall events in the past. This method is simple and easy to be updated, and thus we think this methodology can be adapted to identify vulnerable areas for other environmental disasters.

• Journal of Korean Society for Geospatial Information Science
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• 제12권1호
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• pp.21-29
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• 2004

Floods are disastrous natural phenomena which result in numerous losses of life and property. It is possible to minimize the potential risk by adopting a disaster management system. Nowadays, Geo-Spatial Information System(GSIS) and computer-modelling techniques have assisted scientists and engineers with determining flood disaster assessments, GIS technologies especially have the advantage of performing spatial analysis as well as generating the model for a flood hazard. Therefore, this paper presents the flood management system based on 3D GSIS that can cope with natural disasters actively and manage flood hazard systematically by constructing the database using hydrological data, digital map, DEM, and high-resolution satellite images.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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• pp.617-622
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• 2004

최근의 막대한 인적ㆍ재산적 피해를 초래하고 있는 다양한 자연재해로부터 위험정보의 신속한 취득과 분석을 통해 재해 예방에서 복구에 이르기까지 재난관리를 효과적으로 수행할 수 있는 시스템구축이 요구되고 있다 본 연구에서는 홍수 방재분야에서 보다 현실에 가까운 현황분석을 통한 적극적인 재해 상황 대처와 체계적인 방재관리를 수행하기 위해 수리수문학적 자료와 수치지도, DEM, 고해상 위성영상을 이용하여 데이터베이스를 구축하고 3D GIS를 활용하여 홍수재해를 효과적으로 관리할 수 있는 정보시스템 구축에 대한 방안을 제시하였다.

• Journal of the Earthquake Engineering Society of Korea
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• 제8권6호통권40호
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2016년도 학술발표회
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• pp.89-89
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• 2016

전 세계적으로 발생하는 기후변화로 인해 홍수, 가뭄 등과 같은 자연재해의 빈도가 높아지고 있다. 이러한 자연재해는 사회 경제적으로도 많은 피해를 유발하고 있으며, 특히 물과 관련한 자연재해는 인류의 생존과 직결되는 문제가 된다. 이중에서도 가뭄과 관련한 연구는 진행 속도가 느리고, 가뭄의 진원지나 그 경로를 파악하기 어려운 문제로 인하여 다른 연구와 비교하였을 때 상대적으로 미흡하게 진행되어 왔다. 이러한 문제점 때문에 여타의 다른 자연재해에 비해 가뭄에 대한 예측 및 대책 마련 또한 쉽지 않은 실정이다. 이에 몬테카를로 모의를 통해 미래에 발생할 수 있는 다양한 시나리오를 도출하는 확률론적 접근을 통해 좀 더 효율적이고 현실적인 대책 안을 마련할 수 있다. 본 연구의 목표는 기존 강우생성기와 증발산생성기를 결합한 일기생성기를 개발하고 이를 기후변화 시나리오에 적용하여 미래의 가뭄위험지수를 산출하는 것이다. 산출된 결과를 토대로 우리나라 전역에 대하여 준 실시간으로 갱신되는 미래가뭄위험도의 지도를 제작할 수 있다. 본 연구의 차별성은 첫 번째로 추계론적 접근을 통해 현재의 가뭄상태에 근거한 미래 가뭄에 대한 위험도를 예측할 수 있음을 들 수 있으며, 두 번째로는 지표해석모형을 활용하여 가뭄을 해석하기 때문에 유역 전반에 걸친 토양수분 뿐 만 아니라 국내 주요 댐 상류의 저수지 유입량의 불확실성을 정량화 할 수 있으며, 이는 기후변화에 따른 수자원 장기계획의 수립 및 의사결정에 있어 실용적인 정보를 제공할 수 있다.