• 한국측량학회지
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• 제33권6호
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• pp.579-587
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• 2015

Landslides are major natural geological hazards that result in a large amount of property damage each year, with both direct and indirect costs. Many researchers have produced landslide susceptibility maps using various techniques over the last few decades. This paper presents the landslide susceptibility results from the geographically weighted regression model using remote sensing and geographic information system data for landslide susceptibility in the Inje area of South Korea. Landslide locations were identified from aerial photographs. The eleven landslide-related factors were calculated and extracted from the spatial database and used to analyze landslide susceptibility. Compared with the global logistic regression model, the Akaike Information Criteria was improved by 109.12, the adjusted R-squared was improved from 0.165 to 0.304, and the Moran’s I index of this analysis was improved from 0.4258 to 0.0553. The comparisons of susceptibility obtained from the models show that geographically weighted regression has higher predictive performance.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.71-76
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• 2003

The purpose of this study is the development, application and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence, For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.

• Spatial Information Research
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• 제3권1호
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• pp.81-90
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• 1995

산사태 데이타 베이스 시스템은 과거 산사태 발생자료축척과 통계분석에 의해 향후 산사태 재해대책 수립에 있어서 필요하다. 상기 데이타 시스템은 매년 발생하는 많은 양의 산사태자료를 효율적으로 관리하기 위하여 GIS의 이용이 강조되고 있다. 본 고에서는 과거 산사태 발생지 조사를 기초로 하여 산사태 발생 원인에 따른 산사태 데이타베이스 시스템의 중요성에 대해 설명하고, 산사태 예방을 위한 데이타 베이스 구축을 위해 GIS기술의 도입과 적극 활용에 대해서 기술하였다.

• 지질공학
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• 제32권4호
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• pp.571-583
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• 2022

On 7 August 2020, a large-scale catastrophic landslide was triggered by extreme rainfall at Osan village, Gokseong County, South Jeolla Province, South Korea. The initiation mechanism of the Gokseong landslide was different from those typical landslides that occurred in South Korea. Despite the relatively low elevation and slope degree, the landslide had a long runout distance of about 640 m over a total vertical distance of 90 m. A detailed field investigation and chemical analysis were conducted to understand the possible mechanisms for the high-speed and long-runout behavior of the landslide. The terrain controlled the motion behavior of the landslide and the seepage was observed at the whole landslide body. The clay-rich soils covered on granite bedrock of the landslide deposition area from the rice paddy field to the landslide crown. The results of this study may provide basic data for further research on the mechanisms for landslide initiation and propagation.

• 자원환경지질
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• 제33권4호
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• pp.333-340
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• 2000

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and apply the newly developed techniques for assessment of landslide susceptibility to study areas, Yongin. Landslide locations detected from interpretation of aerial photo and field survey, and topographic, soil and geological maps of the Yongin area were collected. The data of the locations of land-slide, slope, soil texture, topography and lithology were constructed into spatial database using GIS. Using the factors, landslide susceptibility was analyzed by artificial neural network methods. The results of the analysis were verified using the landslide location data. The validation results showed satisfactory agreement between the susceptibility map and landslide location data.

• 지질공학
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• 제32권1호
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• pp.27-40
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• 2022

산사태는 매년 전 세계적으로 상당한 규모의 인명 및 재산 피해를 발생시키고 있다. 따라서 이러한 산사태를 정확하게 예측하는 것은 매우 중요한 일이며 많은 연구자들이 다양한 접근방식을 활용하여 많은 연구를 수행하여 왔다. 산사태 예측과 관련된 분석은 고려되는 영향인자들과 분석되는 위험성의 예측 수준 그리고 산사태 발생 시 예상되는 피해에 대한 고려에 따라 산사태 취약성 분석, 산사태 위험성 분석 그리고 산사태 리스크 분석으로 구분된다. 이들 분석 중 현재 획득 가능한 관련 자료의 수준을 감안하여 국내외적으로 산사태 취약성 분석이 주로 수행되고 있다. 산사태 취약성 분석은 다양한 정성적 및 정량적 분석기법이 적용되어 왔으며 최근 들어서는 예측성능이 우수한 것으로 알려진 물리사면모델을 활용한 분석기법이 폭넓게 사용되고 있다. 특히 물리사면모델은 산사태 발생 이력의 존재여부와 상관없이 적용이 가능하고 산사태 발생 프로세스를 재현할 수 있다는 장점을 가지고 있다. 따라서 본 논문에서는 물리사면모델을 활용한 취약성 분석기법에 대하여 검토해 보았다.

• 한국지형학회지
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• 제27권3호
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors 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 the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• 한국지리정보학회지
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• 제15권1호
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• pp.119-132
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• 2012

최근 급증하고 있는 국지성 집중호우로 인해 급경사지를 중심으로 산지토사재해가 빈발하고 있으며 이에 대한 예방과 취약지역 분석을 위해 산사태 위험지도의 중요성이 부각되고 있다. 본 연구에서는 산지하천유역의 토사재해 위험지역 분석을 목적으로 수자원지리정보시스템 기반의 HyGIS-Landslide 콤포넌트를 개발하였다. HyGIS-Landslide는 산림청의 산사태 위험지 판정기준 및 등급기준을 토대로 수치공간자료의 연산결과를 분류한 후 산사태 위험성을 제시하도록 설계되었으며 위험지 판정기준의 가중치를 사용자가 재 설정할 수 있도록 구현하여 산사태 발생공간의 지역적 특성을 반영할 수 있도록 하였다. 본 콤포넌트에서는 사용자가 원하는 지역을 대상으로 현시성 있는 공간자료를 활용할 수 있으며 조사자의 점수보정 과정을 반영하여 시스템 활용성을 높이고자 하였다. HyGIS-Landslide는 HyGIS가 제공하는 지형분석 기능을 통해 사용자 편의를 확보할 수 있으며 산사태 발생구역도와의 중첩연산을 통해 위험지 분류결과의 검증이 가능하다. 본 연구에서는 강원도 인제군의 시험유역을 대상으로 HyGIS-Landslide를 적용하였으며 산사태 맵핑결과와의 중첩비교를 통해 모형의 활용성을 평가하고 위험지 판정기준의 가중치를 재조정하여 위험지역을 보다 효과적으로 분류할 수 있음을 제시하였다.

• 자원환경지질
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• 제33권6호
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• pp.547-556
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• 2000

The purpose of this study is to analyze shear fracture system using landslide location occurred 1998 at Janghung area. For the geological implication, foliation was surveyed and analyzed, and location of landslide, geological structure and topography were constructed into spatial database using GIS. With the constructed spatial database, shear fracture system was assessed by the relation analysis between strike and dip of the foliation and aspect and slope of the topography. We compared strike and dip of foliation and aspect and slope of topography and recognized the typical fracture pattern, strike and dip of joint, that coincided with shear fracture system. The result tells us that foliation of gneiss has geometrical relation to joint or fault that leading landslide. GIS was used to analyze vast data efficiently and the result can be used to assess the landslide susceptibility as important factor.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.547-550
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• 2006

This study is to suggest a methodology to produce landslide hazard map by combining LRA (Logistic Regression Analysis) and AHP (Analytic Hierarchy Program) Approach. Topographic factors (slope, aspect, elevation), soil drain, soil depth and land use were adopted to classify landslide hazard areas. The method was applied to a 520 $km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9 % matching rate for the real landslide sites comparing with the classified areas of high-risk landslide while LRA and AHP showed 46.1 % and 48.7 % matching rates respectively.