• Title/Summary/Keyword: evaluation chart of landslide susceptibility

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Development of an Evaluation Chart for Landslide Susceptibility using the AHP Analysis Method (AHP 분석기법을 이용한 급경사지재해 취약성 평가표 개발)

  • Chae, Byung-Gon;Cho, Yong-Chan;Song, Young-Suk;Seo, Yong-Seok
    • The Journal of Engineering Geology
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    • v.19 no.1
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    • pp.99-108
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    • 2009
  • Since the preexisting evaluation methods of landslide susceptibility take somehow long time to determine the slope stability based on the field survey and laboratory analysis, there are several problems to acquire immediate evaluation results in the field. In order to overcome the previously mentioned problems and incorrect evaluation results induced by some subjective evaluation criteria and methods, this study tried to develop a method of landslide susceptibility by a quantitative and objective evaluation approach based on the field survey. Therefore, this study developed an evaluation chart for landslide susceptibility on natural terrain using the AHP analysis method to predict landslide hazards on the field sites. The AHP analysis was performed by a questionnaire to several specialists who understands mechanism and influential factors of landslide. Based on the questionnaire, weighting values of criteria and alternatives to influence landslide triggering were determined by the AHP analysis. According to the scoring results of the analysed weighting values, slope angle is the most significant factor. Permeability, water contents, porosity, lithology, and elevation have the significance to the landslide susceptibility in a descending order. Based on the assigned scores of each criterion and alternatives of the criteria, an evaluation chart for landslide susceptibility was suggested. The evaluation chart makes it possible for a geologist to evaluate landslide susceptibility with a total score summed up each alternative score.

Suggestion of an Evaluation Chart for Landslide Susceptibility using a Quantification Analysis based on Canonical Correlation (정준상관 기반의 수량화분석에 의한 산사태 취약성 평가기법 제안)

  • Chae, Byung-Gon;Seo, Yong-Seok
    • Economic and Environmental Geology
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    • v.43 no.4
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    • pp.381-391
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    • 2010
  • Probabilistic prediction methods of landslides which have been developed in recent can be reliable with premise of detailed survey and analysis based on deep and special knowledge. However, landslide susceptibility should also be analyzed with some reliable and simple methods by various people such as government officials and engineering geologists who do not have deep statistical knowledge at the moment of hazards. Therefore, this study suggests an evaluation chart of landslide susceptibility with high reliability drawn by accurate statistical approaches, which the chart can be understood easily and utilized for both specialists and non-specialists. The evaluation chart was developed by a quantification method based on canonical correlation analysis using the data of geology, topography, and soil property of landslides in Korea. This study analyzed field data and laboratory test results and determined influential factors and rating values of each factor. The quantification analysis result shows that slope angle has the highest significance among the factors and elevation, permeability coefficient, porosity, lithology, and dry density are important in descending order. Based on the score assigned to each evaluation factor, an evaluation chart of landslide susceptibility was developed with rating values in each class of a factor. It is possible for an analyst to identify susceptibility degree of a landslide by checking each property of an evaluation factor and calculating sum of the rating values. This result can also be used to draw landslide susceptibility maps based on GIS techniques.

Landslide Susceptibility Evaluation in Yanbian Region

  • Liu, Xiuxuan;Quan, Hechun;Moon, Hongduk;Jin, Guangri
    • Journal of the Korean GEO-environmental Society
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    • v.18 no.2
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    • pp.21-27
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    • 2017
  • In order to evaluate landslide susceptibility in Yanbian region, this study analyzed 7 factors related to landslide occurrence, such as soil, geology, land use, slope, slope aspect, fault and river by Analytic Hierarchy Process (AHP), and calculated the weights of these 7 hazard-induced factors, determined the internal weights and the relative weights between various factors. According to these weights, combining the Remote Sensing technology (RS) with Geographic Information System technology (GIS), the selected area was evaluated by using GIS raster data analysis function, then landslide susceptibility chart was mapped out. The comprehensive analysis of AHP and GIS showed that there has unstable area with the potential risk of sliding in the research area. The result of landslide susceptibility agrees well with the historical landslides, which proves the accuracy of adopted methods and hazard-induced factors.

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.