GIS와 확률론적 해석을 적용한 산사태 취약성 평가 : 보은지역 사례를 중심으로 = Susceptibility assessment of landslide using GIS and probabilistic analysis : case study for Boeun area

다국어 초록 (Multilingual Abstract)

Since the occurrence of landslide is affected by many different spatial and climatic factors such as geology, geomorphology, vegetation and rainfall, it is difficult to predict and assess its hazard. Therefore, several researches have been carried out, especially based on Geographic Information System(GIS). However, the GIS techniques used in many previous studies consider only the statistics of occurrence and the related factors, not the mechanical analysis of the failure mechanism.
The objective of this study is to suggest an assessment method for landslide susceptibility in regional area using GIS and Monte Carlo Simulation(MCS) which is commonly used as a probabilistic analysis. Boeun in Chungcheongbuk-do was selected as the study area. And its spatial data were obtained to construct the spatial database for input data. The geotechnical parameters for susceptibility assessment of landslide were obtained from field and analyzed to minimize the intrinsic uncertainties. The cohesion and internal friction angle were considered as random variables and their probability characteristics were obtained from field samples. Then using MCS, the probability of failure for each grid was evaluated instead of safety factor.
From the results of the susceptibility assessment of landslide, when the criteria is set as 5% for the probability of failure in landslide, the analysis provides an appropriate result comparing to field conditions. However, as the criteria is increased, the accuracy of results is decreased. In addition, as the coefficients of variation for random variables are increased, the degree of prediction accuracy is also increased. That is, 30% of the coefficient of variation is appropriate to improve the reliability and reduce the uncertainties if field data are not available.
The assessment results for susceptibility of landslide were applied to Boeun area and checked its feasibility. Since MCS technique effectively deals with uncertainties and random properties of input parameters, the probabilistic analysis shows more accurate results than conventional deterministic analysis methods. Moreover, It can be effectively utilized any region where the GIS data were established using MCS module presented here.

목차 (Table of Contents)

• 제 1 장 서 론 1
• 1.1 연구배경 및 목적 1
• 1.2 연구동향 5
• 1.3 연구내용 및 방법 8
• 1.4 연구범위 10
• 제 2 장 이론적 배경 11
• 2.1 산사태 기본이론 11
• 2.1.1 산사태의 정의 및 원인 11
• 2.1.2 산사태 분류 13
• 2.1.3 토석류 19
• 2.1.4 국내 산사태의 유형 20
• 2.2 지리정보시스템 21
• 2.2.1 개요 21
• 2.2.2 GIS의 기능 22
• 2.2.3 GIS의 구성요소 24
• 2.2.4 GIS의 활용분야 25
• 2.3 확률론의 기본개념 28
• 2.3.1 확률변수 29
• 2.3.2 확률밀도함수 30
• 2.3.3 평균 및 표준편차 32
• 2.3.4 정규성 검정 33
• 2.4 산사태 해석모델 36
• 2.4.1 개요 36
• 2.4.2 무한사면 해석모델 37
• 2.4.3 안전율 및 파괴확률 38
• 2.5 GIS를 활용한 산사태 취약성 분석 41
• 2.5.1 결정론적 방법 41
• 2.5.2 확률론적 방법 42
• 2.5.3 SINMAP 방법 46
• 제 3 장 연구대상 현장조사 및 확률특성 분석 47
• 3.1 연구지역 47
• 3.1.1 지형 및 지질 47
• 3.1.2 산사태 피해현황 48
• 3.2 현장조사 및 시료채취 50
• 3.2.1 현장조사 50
• 3.2.2 시료채취 52
• 3.3 실내시험 결과 53
• 3.4 지반정수의 확률적 특성 분석 56
• 3.4.1 확률적 특성 획득 56
• 3.4.2 정규성 검정결과 59
• 제 4 장 GIS 자료구축 및 확률론적 해석기법 적용 61
• 4.1 공간 데이터베이스 구축 61
• 4.1.1 산사태 발생위치 데이터베이스 61
• 4.1.2 지형 관련 데이터베이스 62
• 4.1.3 토양 관련 데이터베이스 63
• 4.1.4 지반정수 관련 데이터베이스 64
• 4.2 몬테카를로 시뮬레이션(MCS)모듈 개발 및 적용 66
• 제 5 장 산사태 취약성 평가 69
• 5.1 확률론적 해석 69
• 5.1.1 지하수위 변화에 따른 파괴확률 분포 70
• 5.1.2 파괴확률 기준에 따른 해석 89
• 5.1.3 변동계수 기준에 따른 해석 93
• 5.2 결정론적 해석 100
• 5.3 SINMAP을 이용한 해석 104
• 5.4 적용성 분석 108
• 5.4.1 확률론적 해석결과의 적용성 108
• 5.4.2 파괴확률 기준에 따른 적용성 109
• 5.4.3 변동계수 기준에 따른 적용성 110
• 제 6 장 결 론 112
• 참고문헌 114