• Title/Summary/Keyword: landslide susceptibility analysis

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An Assessment of Ecological Risk by Landslide Susceptibility in Bukhansan National Park (산사태취약성 분석을 통한 북한산국립공원의 생태적 위험도 평가)

  • Kim, Kyung-Tae;Jung, Sung-Gwan;You, Ju-Han;Jang, Gab-Sue
    • 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.

Comparison between Models for Thickness of Soils (토심추정 모형의 비교)

  • Min, Chang-Sik;Jang, Byeong-Uk;Cha, Gyeong-Seop
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2005.10a
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    • pp.399-403
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    • 2005
  • Slope angle, ground water table and thickness of soils are the key factors affecting landslide stability. However examining the factors such as thickness of soils; geological structure, slope angle, and height, in order to use the global landslide susceptibility forecasting analysis is very expensive and time consuming effort. So most researchers prefer to use the simplest methods such as the C strata and the USGS methods. In this research thickness of soils was calculated using these two methods and stability analysis was performed with the thickness of soils calculated by the two methods at the SINMAP based on ArcView 3.2. The two safety factor maps were compared with the past landslide records. The thickness of soils calculated by USGS method showed more unstable safety factors.

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Analysis of Landslide Factors Using Geo-Spatial Information System and Analytic Hierarchy Process (GSIS와 AHP법을 이용한 산사태 유발인자 분석)

  • 양인태;김제천;천기선;김동문
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.19 no.3
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    • pp.273-281
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    • 2001
  • The landslide occurrence in Sam-Chuck area was analyzed through Geo-Spatial Information System and AHP(Analytic Hierarchy Process). Among many factors which causes landslide, terrain slope, terrain aspect, lithology, soil texture and vegetation arc taken as input data from existing maps and constructed as a database. These factors are determined by each environmental factor by environmental and geological characters in the study area, and the rating and weight about factor are input using AHP. Possible areas for landslide have been extracted by overlaying each layers. Finally, the estimated results are compared with real landslide sites to know which factor is the most effective for landslide. The results showed that lithology and soil factor have high susceptibility in Sam-Chuck area.

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Evaluation and Analysis of Gwangwon-do Landslide Susceptibility Using Logistic Regression (로지스틱 회귀분석 기법을 이용한 강원도 산사태 취약성 평가 및 분석)

  • Yeon, Young-Kwang
    • Journal of the Korean Association of Geographic Information Studies
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    • v.14 no.4
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    • pp.116-127
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    • 2011
  • This study conducted landslide susceptibility analysis using logistic regression. The performance of prediction model needs to be evaluated considering two aspects such as a goodness of fit and a prediction accuracy. Thus to gain more objective prediction results in this study, the prediction performance of the applied model was evaluated considering two such evaluation aspects. The selected study area is located between Inje-eup and Buk-myeon in the middle of Kwangwon. Landslides in the study area were caused by heavy rain in 2006. Landslide causal factors were extracted from topographic map, forest map and soil map. The evaluation of prediction model was assessed based on the area under the curve of the cumulative gain chart. From the results of experiments, 87.9% in the goodness of fit and 84.8% in the cross validation were evaluated, showing good prediction accuracies and not big difference between the results of the two evaluation methods. The results can be interpreted in terms of the use of environmental factors which are highly related to landslide occurrences and the accuracy of the prediction model.

Weight Determination of Landslide Factors Using Artificial Neural Networks (인공신경 망을 이용한 산사태 발생요인의 가중치 결정)

  • 류주형;이사로;원중선
    • Economic and Environmental Geology
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    • v.35 no.1
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    • pp.67-74
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    • 2002
  • The purpose of this study is to determine the weights of the factors for landslide susceptibility analysis using artificial neural network. Landslide locations were identified from interpretation of aerial photographs, field survey data, and topography. The landslide-related factors such as topographic slope, topographic curvature, soil drainage, soil effective thickness, soil texture, wood age and wood diameter were extracted from the spatial database in study area, Yongin. Using these factors, the weights of neural networks were calculated by backpropagation training algorithm and were used to determine the weight of landslide factors. Therefore, by interpreting the weights after training, the weight of each landslide factor can be ranked based on its contribution to the classification. The highest weight is topographic slope that is 5.33 and topographic curvature and soil texture are 1 and 1.17, respectively. Weight determination using backprogpagation algorithms can be used for overlay analysis of GIS so the factor that have low weight can be excluded in future analysis to save computation time.

Assessment of Landslide Susceptibility of Physically Based Model Considering Characteristics of the Unsaturated Soil (불포화지반 특성을 고려한 물리적 사면 모델 기반의 산사태 취약성 분석)

  • Kim, Jin Seok;Park, Hyuck Jin
    • Economic and Environmental Geology
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    • v.47 no.1
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    • pp.49-59
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    • 2014
  • Rainfall-induced landslides are caused by reduction of effective stress and shear strength due to rainfall infiltration. In order to analyze the susceptibility of landslides, the statistical analysis approach has been used widely but this approach has the limitation which cannot take into account of landslide triggering mechanism. Therefore, the physically based model which can consider the process of landslide occurrence was proposed and commonly used. However, the most previous physically based model analyses evaluate and consider the strength characteristics for saturated soil only in the susceptibility analysis. But the strength parameters for unsaturated soil such as matric suction should be considered with the strength parameters for saturated soil since the shear strength in unsaturated soil also plays important role in the stability of slope. Consequently this study suggested the modified physically based slope model which can evaluate strength characteristics for both of saturated and unsaturated soils. In addition, this study evaluated the thickness of saturated part in slope with rainfall intensity and hydraulic characteristics of slope on the basis of physically based model. In order to evaluate the feasibility, the proposed model was applied to practical example in Jinbu area, Gangwon-do, which was experienced large amount of landslides in July 2006. The ROC graph analysis was used to evaluate the validation of the model, and the analysis results were compared with the results of the previous analysis approach.

Prediction of Landslides Occurrence Probability under Climate Change using MaxEnt Model (MaxEnt 모형을 이용한 기후변화에 따른 산사태 발생가능성 예측)

  • Kim, Hogul;Lee, Dong-Kun;Mo, Yongwon;Kil, Sungho;Park, Chan;Lee, Soojae
    • Journal of Environmental Impact Assessment
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    • v.22 no.1
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    • pp.39-50
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    • 2013
  • Occurrence of landslides has been increasing due to extreme weather events(e.g. heavy rainfall, torrential rains) by climate change. Pyeongchang, Korea had seriously been damaged by landslides caused by a typhoon, Ewiniar in 2006. Moreover, the frequency and intensity of landslides are increasing in summer due to torrential rain. Therefore, risk assessment and adaptation measure is urgently needed to build resilience. To support landslide adaptation measures, this study predicted landslides occurrence using MaxEnt model and suggested susceptibility map of landslides. Precipitation data of RCP 8.5 Climate change scenarios were used to analyze an impact of increase in rainfall in the future. In 2050 and 2090, the probability of landslides occurrence was predicted to increase. These were due to an increase in heavy rainfall and cumulative rainfall. As a result of analysis, factors that has major impact on landslide appeared to be climate factors, prediction accuracy of the model was very high(92%). In the future Pyeongchang will have serious rainfall compare to 2006 and more intense landslides area expected to increase. This study will help to establish adaptation measure against landslides due to heavy rainfall.

Prediction of Landslide around Stone Relics of Jinjeon-saji Area (진전사지 석조문화재 주변의 산사태예측)

  • Kim, Kyeong-Su;Lee, Choon-Oh;Song, Young-Suk;Cho, Yong-Chan
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.03a
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    • pp.1378-1385
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    • 2008
  • The probability of landslide hazards was predicted to natural terrain around the stone relics of Jinjeon-saji area, which is located in Yangyang, Kangwon Province. As the analysis results of field investigation, laboratory test and geology and geomorphology data, the effect factors of landslides occurrence were evaluated, and then the landslides prediction map was made up by use of prediction model considering the effect factors. The susceptibility of stone relics induced by landslides was investigated as the grading classification of occurrence probability using the landslides prediction map. In the landslides prediction map, the high probability area of landslides over 70% of occurrence probability was 3,489m3, which was 10.1% of total prediction area. If landslides are occurred at the high elevation area, the three stories stone pagoda of Jinjeon-saji (National treasure No.122) and the stone lantern of Jinjeon-saji (Treasure No.439) will be collapsed by debris flow.

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Study on Landslide using GIS and Remote Sensing at the Kangneung Area($\textrm{I}$) -Relationship Analysis between Landslide Location and Related Factors (GIS와 원격탐사를 이용한 강릉지역 산사태 연구($\textrm{I}$) -산사태 발생 위치와 영향 인자와의 상관관계 분석)

  • 이명진;이사로;원중선
    • Economic and Environmental Geology
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    • v.37 no.4
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    • pp.425-436
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    • 2004
  • The purpose of this study is to analyze the spatial relationship between the landslides occurred by typhoon, Rusa in 2002 and geospatial dataset. Landslide locations were detected using satellite image and field survey. Topogra-phy, soil, forest, geology and land use data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, type of topography, texture, material, drainage, effective thickness of soil, type, age, diameter, density of wood, lithology, lineament of geology, land use and lineament were used as the land-slide occurrence factors. Using a frequence ratio model, the spatial relationships between the landslides and the factors were extracted. The spatial relationships is helpful to explain the characteristics of the landslide, and to make landslide susceptibility map.

Assessment of Earthquake Induced Landslide Susceptibility with Variation of Groundwater Level (지하수위 변화에 따른 지진 유발 산사태의 취약섬 분석)

  • Kim, Ji-Seok;Park, Hyuek-Jin;Lee, Jung-Hyun
    • Economic and Environmental Geology
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    • v.44 no.4
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    • pp.289-302
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    • 2011
  • Since the frequency of the earthquake occurrence in Korean peninsular is continuously increasing, the possibility that massive landslides are triggered by earthquake is also growing in Korea. Previously, the landslide is known to be induced by large magnitude earthquake, whose magnitude is larger than 6.0. However, the landslide can be induced by only small magnitude earthquake, especially in the fully saturated soil. Therefore, the susceptibility of landslide caused by small magnitude earthquake in fully saturated soil is analyzed in this study. For that, the topographical and geological characteristics of the site were obtained and managed by GIS software. In the procedure of the study, slope angle, cohesion, friction angle, unit weight of soil were obtained and constructed as a spatial database layer. Combining these data sets in a dynamic model based on Newmark's displacement analysis, the landslide displacements were estimated in each grid cell. In order to check out the possibility of the earthquake induced landslides, the level of the groundwater table is varied from dry to 80% saturated soil. In addition, in order to analyze the effect of the magnitude of earthquake and distance to epicenter, four different earthquakes epicenters were considered in the study area.