• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.373-383
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• 2006

The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.599-606
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• 2015

Damage of landslide due to earthquake covers a considerable part of total damage due to earthquake. Landslide due to earthquake affects direct damage of human lives and structures, and social system can be paralyzed by losing functions of roads, basic industries, and so on. Therefore, systematic and specialized research examining the factors affecting the slope stability by earthquakes should be needed. However, method of evaluation of slope stability problems due to earthquake contains somewhat uncertainty since many soil properties are predicted or assumed. In this study, influences of change of soil properties such as degree of saturation and cohesion value are analyzed in factor of safety and displacement using seismic landslide hazard maps based on GIS. As the degree of saturation increases or cohesion decreases, it is found that seismic landslide hazard area marked with factors of safety or displacements tends to increase. Therefore, to draw more exact landslide hazard map during earthquake, it is necessary to obtain accurate soil property information preferentially from site investigation data in the field.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.03a
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• pp.509-516
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• 2001

As the first step for the application of seismic landslide hazard maps to domestic cases, two types of hazard maps on Ul-joo from pseudostatic analysis and Newmark sliding block analysis are constructed and comllared. Arcview, the GIS program and the 1:5,000 digital maps of the test-site are used for the construction of hazard maps and tile parameters for the analyses are determined by seismic survey and laboratory tests. The results from the pseudostatic analysis have more conservative values of lower critical slope angles, although the results from the two different analyses have similar tendencies. In detail, with increasing the peak ground acceleration, the difference between the two analyses in the critical slope angle increases, while the difference decreases with increasing the maximum soil depth.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.4
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• pp.17-24
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• 2015

This study utilized high quality three-dimensional geospatial information produced by high-resolution Digital Aerial Photograph and Airborne LiDAR data in order to analyse landslides and debris flows induced by the heavy rainfall in Chuncheon area. Also, this study analysed correlation between the established landslide hazard map and the landslide factor effect and reviewed the analysis result of debris flows on the area where landslides with debris flows occurred frequently. Finally;the study proposed ways to renew the established landslide hazard map effectively and utilize the high quality three-dimensional Geospatial information on the landslide risk area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.861-867
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• 2006

The objective of this study is to analyze the landslide hazard areas by combining LRA (Lgistic Regression Analysis) and AHP (Analytic Hierarchy Program) methods with Remote Sensing and GIS data in Anseong-si. In order to classify landslide hazard areas of seven levels, six topographic factors (slope, aspect, elevation, soil drain, soil depth, and land use) were used as input factors of LRA and AHP methods. As results, high-risk areas for landslide (1 and 2 levels) by LRA and AHP of its own were classified as 46.1% and 48.7%, respectively. A new method by applying weighting factors to the results of LRA and AHP was suggested. High-risk areas for landslide (1 and 2 levels) form the new method was classified as 58.9%.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.259-262
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• 2007

In our country it develop damage reduction and prediction technology for prevention the danger of the rockfall and landslide which is repeated yearly. And it constructs integrated and efficient the misfortune management system it will be able to manage. So we will accomplish aims that is the rockfall and landslide damage occurrence reduction.

• Journal of the Korean Geotechnical Society
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• v.28 no.4
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• pp.23-33
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• 2012

Recently, landslide disasters caused by severe rain storms and typhoons have been frequently reported. Due to the geomorphologic characteristics of Korea, considerable portion of urban area and infrastructures such as road and railway have been constructed near mountains. These infrastructures may encounter the risk of landslide and debris flow. It is important to evaluate the highly risky locations of landslide and to prepare measures for the protection of landslide in the process of construction planning. In this study, a landslide-risk prediction equation is proposed based on the statistical analysis of 423 landslide data set obtained from field surveys, disaster reports on national road, and digital maps of landslide area. Each dataset includes geomorphologic characteristics, soil properties, rainfall information, forest properties and hazard history. The comparison between the result of proposed equation and actual occurrence of landslide shows 92 percent in the accuracy of classification. Since the input for the equation can be provided within short period and low cost, and the results of equation can be easily incorporated with hazard map, the proposed equation can be effectively utilized in the analysis of landslide-risk for large mountainous area.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.694-709
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• 2021

Purpose: In this study, earthquake-induced landslide risk assessment was conducted to provide basic data for efficient and preemptive damage prevention by selecting the erosion control work before the earthquake and the prediction and restoration priorities of the damaged area after the earthquake. Method: The study analyzed the previous studies abroad to examine the evaluation methodology and to derive the evaluation factors, and examine the utilization of the landslide hazard map currently used in Korea. In addition, the earthquake-induced landslide hazard map was also established on a pilot basis based on the fault zone and epicenter of Pohang using seismic attenuation. Result: The earthquake-induced landslide risk assessment study showed that China ranked 44%, Italy 16%, the U.S. 15%, Japan 10%, and Taiwan 8%. As for the evaluation method, the statistical model was the most common at 59%, and the physical model was found at 23%. The factors frequently used in the statistical model were altitude, distance from the fault, gradient, slope aspect, country rock, and topographic curvature. Since Korea's landslide hazard map reflects topography, geology, and forest floor conditions, it has been shown that it is reasonable to evaluate the risk of earthquake-induced landslides using it. As a result of evaluating the risk of landslides based on the fault zone and epicenter in the Pohang area, the risk grade was changed to reflect the impact of the earthquake. Conclusion: It is effective to use the landslide hazard map to evaluate the risk of earthquake-induced landslides at the regional scale. The risk map based on the fault zone is effective when used in the selection of a target site for preventive erosion control work to prevent damage from earthquake-induced landslides. In addition, the risk map based on the epicenter can be used for efficient follow-up management in order to prioritize damage prevention measures, such as to investigate the current status of landslide damage after an earthquake, or to restore the damaged area.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• Journal of the Korean GEO-environmental Society
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• v.20 no.6
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• pp.15-22
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• 2019

In this study, the hazard areas are identified by using the Newmark displacement model, which is a predictive model for identifying the areas at risk of landslide triggered by earthquakes, based on the results of field survey and laboratory test, and literature data. The Newmark displacement model mainly utilizes earthquake and slope related data, and the safety of slope stability derived from LSMAP, which is a landslide prediction program. Backyang Mt. in Busan where the landslide has already occurred, was chosen as the study area of this research. As a result of this study, the area of landslide prone zone identified by using the Newmark displacement model without earthquake factor is about 1.15 times larger than that identified by using LSMAP.