• 한국지반신소재학회논문집
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• 제12권2호
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• pp.67-74
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• 2013

본 연구에서는 의사결정나무모형을 적용하여 개발된 급경사지재해 예측프로그램 SHAPP ver 1.0을 이용하여 강원도 횡성군 우천면 하대리 일대 영동고속도로 주변에 대한 급경사지재해 예측을 실시하였다. 이를 위하여 먼저 대상지역의 총 10개소에서 토층시료를 채취하고, 이에 대한 토질시험을 실시하였다. 대상지역에 대한 토질시험결과를 토대로 투수계수와 간극비에 대한 주제도를 작성하고 수치지형도를 이용하여 지형의 경사분석을 실시하였다. 이를 이용하여 급경사지재해 예측을 실시한 결과 총 27,776개의 해석셀 가운데 2,120개의 셀에서 급경사지재해가 발생될 것으로 예측되었다. 이때 해석셀의 크기는 $5m{\times}5m$이므로 급경사지재해 발생예상 면적은 $53,000m^2$으로 나타났다.

• 한국방재학회 논문집
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• 제10권6호
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• pp.73-80
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• 2010

최저 안전율 또는 최대 파괴확률을 기반으로 하는 기존의 사면안정해석에 대하여, 지반물성과 해석모델이 갖는 고유 불확실성을 최소화하고, 사면안정해석에서 다양한 안정해석모델과 그에 따른 파괴형상을 반영할 수 있도록, 다중 파괴모드를 고려한 사면의 신뢰성해석기법을 제안하였다. 파괴확률의 산정에는 체계 신뢰성해석분야에서 최근 도입된 선형계획법에 의한 최적화를 이용하였다. 이를 통하여 여러 가지 해석모델을 신뢰성 기반으로 동시에 고려하여 해석할 수 있다. 선형계획법에 의한 다중 파괴 모드를 고려한 파괴확률 산정기법을 이용하여 단순 사면의 경사도 결정을 위한 최적 설계를 검토하였다. 그 결과, 동시 파괴확률을 이용하면, 대상으로 하는 사면안정해석모델과 파괴형상 및 파괴확률을 복합적으로 고려할 수 있기 때문에 개선된 안전성을 확보할 수 있을 것으로 판단된다.

• 지질공학
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• 제18권3호
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• pp.303-309
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• 2008

중요 석조문화재가 위치하고 있는 강원도 양양군 소재 진전사지 주변지역에 대한 사면재해 가능성을 예측하였다. 연구지역에 대한 현장조사, 실내시험, 지질 및 지형자료 분석을 통해 산사태에 유의한 영향요소를 평가하고 그 자료들을 예측모델에 적용하여 산사태예측도를 작성하였다. 그리고 산사태예측도에 의해 발생확률을 등급별로 분류함으로써 산사태로 인한 석조문화재의 피해가능성을 검토하였다. 산사태예측도에 의하면, 발생확률 70% 이상으로 산사태가 발생될 가능성이 높은 지역은 대상면적의 10.1%인 $3,489m^2$정도로 비교적 넓은 면적비율을 나타내었다. 피해영향권에 속한 높은 고도의 산사면에서 산사태가 발생할 경우 국보 제122호인 진전사지삼층석탑과 보물 제439호인 진전사지부도에 사태물질로 인한 피해가능성이 예상된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.129-131
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• 2003

The aim of this study is to evaluate the hazard of landslides at Penang, Malaysia, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys. The topographic and geologic data and satellite image were collected, processed and constructed into a spatial database using GIS and image processing. The used factors that influence landslide occurrence are topographic slope, topographic aspect topographic curv ature and distance from drainage from topographic database, geology and distance from lineament from the geologic database, land use from TM satellite image and vegetation index value from SPOT satellite image. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by probability - likelihood ratio - method. The results of the analysis were verified using the landslide location data. The validation results showed satisfactory agreement between the hazard map and the existing data on landslide location.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.65-70
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• 2003

The weight-of-evidence model one of the Bayesian probability model was applied to the task of evaluating landslide susceptibility using GIS. Using the location of the landslides and spatial database such as topography, soil, forest, geology, land use and lineament, the weight-of-evidence model was applied to calculate each factor's rating at Boun area in Korea where suffered substantial landslide damage fellowing heavy rain in 1998, The factors are slope, aspect and curvature from the topographic database, soil texture, soil material, soil drainage, soil effective thickness, and topographic type from the soil database, forest type, timber diameter, timber age and forest density from the forest map, lithology from the geological database, land use from Landsat TM satellite image and lineament from IRS satellite image. Tests of conditional independence were performed for the selection of the factors, allowing the 43 combinations of factors to be analyzed. For the analysis, the contrast value, W$\^$＋/and W$\^$-/, as each factor's rating, were overlaid to map laudslide susceptibility. The results of the analysis were validated using the observed landslide locations, and among the combinations, the combination of slope, curvature, topographic, timber diameter, geology and lineament show the best results. The results can be used for hazard prevention and planning land use and construction

• 한국지형학회지
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• 제27권2호
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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.

• 자원환경지질
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• 제33권4호
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• pp.321-332
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• 2000

The purpose of this study is to analyze landslide that occurred in Yongin area in 1991 using spatial database. For this, landslide locations are detected from aerial photographs interpretation and field survey. The locations of landslide, topography, soil, forest and geology were constructed to spatial database using Geographic Information System (GIS). To establish occurrence factors of landslide, slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective thickness of soil were extracted from the soil database, and type, age, diameter and density of wood were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the TM satellite image. Landslide was analyzed using spatial correlation between the landslide and the landslide occurrence factors by bivariate probability methods. GIS was used to analyze vast data efficiently and statistical programs were used to maintain specialty and accuracy. The result can be used to prevention of hazard, land use planning and construction planning as basic data.

• 한국방재학회 논문집
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• 제10권4호
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• pp.81-88
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• 2010

최근 들어 기상 이변에 따라 단시간 동안에 특정 소유역에 집중하는 호우 또는 초과우량에 의한 국지성 돌발홍수가 빈번히 발생함에 따라, 이로 인한 인명과 재산의 상당한 위험과 손실은 전 세계적인 것으로서 우리나라도 증가일로에 있다. 돌발홍수는 일반적으로 급경사 소유역에서 집중적인 강우에 의해 발생하여 빠른 유출과 토석류를 동반하기 때문에, 홍수피해를 대비하기 위한 사전 홍수예보시간이 부족할 정도로 급격히 빠른 홍수의 특성을 보인다. 본 연구의 목적은 대상유역의 확률강우량으로부터 돌발홍수지수(flash flood index, FFI)를 산정하여 돌발홍수의 심각성 정도를 정량적으로 분석하고자 한다. 특히 미계측 유역하천에서의 지역 홍수예 경보를 위한 기초자료를 제공할 수 있도록, 대상유역에 대하여 상대적인 돌발홍수심도를 제시할 수 있는 FFI-D-F(돌발홍수지수-지속시간-빈도) 관계곡선을 개발하였다. 또한 FFI-D-F 관계곡선은 현존 및 계획 방재시설물의 돌발홍수 대응능력 및 잔여홍수위험 평가에 활용될 수 있을 것으로 기대된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.314-317
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• 2004

The aim of this study was to evaluate the susceptibility from landslides in the Lai Chau region of Vietnam, using Geographic Information System (GIS) and remote sensing data, focusing on the relationship between tectonic fractures and landslides. Landslide locations were identified from an interpretation of aerial photographs and field surveys. Topographic and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image processing techniques, and a scheme of the tectonic fracturing of the crust in the Lai Chau region was established. In this scheme, Lai Chau was identified as a region with low crustal fractures, with the grade of tectonic fracture having a close relationship with landslide occurrence. The factors found to influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature, distance from drainage, lithology, distance from a tectonic fracture and land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability-likelihood ratio method. The results of the analysis were verified using landslide location data, and these showed a satisfactory agreement between the hazard map and existing landslide location data.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.717-720
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• 2006

In this study, we predicted locations vulnerable to ground subsidence hazard using fuzzy logic and geographic information system (GIS). Test was carried out at an abandoned underground coal mine in Samcheok City, Korea. Estimation of relative ratings of eight major factors influencing subsidence and determination of effective fuzzy operators are presented. Eight major factors causing ground subsidence were extracted and constructed as a spatial database using the spatial analysis and the probability analysis functions. The eight factors include geology, slope, landuse, depth of mined tunnel, distance from mined tunnel, RMR, permeability, and depth of ground water. A frequency ratio model was applied to calculate relative rating of each factor, and the ratings were integrated using fuzzy membership function and five different fuzzy operators to produce a ground subsidence susceptibility map. The ground subsidence susceptibility map was verified by comparing it with the existing ground subsidences. The obtained susceptibility map well agreed with the actual ground subsidence areas. Especially, ${\gamma}-operator$ and algebraic product operator were the most effective among the tested fuzzy operators.