• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.2
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• pp.33-45
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• 2011

The purpose of this study to analyze landslide-triggering factors using the 38 landslide cases occurred by typhoon, Rusa in 2002, Maemi in 2003 and Ewiniar in 2006 and geospatial characteristics in Hamyang and Geochang County. where two day's heavy rainfall was concentrated on. The rainfalls factors to trigger landslides were accumulative rainfall (>230mm) and rainfall intensity(>30-75mm). The highest landslide frequency was concentrated on the areas of 400-900m in height and on the slopes of $25-40^{\circ}$ in degree. The frequency of landslide was high exceedingly above 80% of a slope attitude, while the frequency is very low below 70%. Granite was more susceptible as much as 9 times than metamorphic rocks. In areas mixed soil with gravels and rock blocks, the frequency of landslide was 73%.

• Journal of The Geomorphological Association of Korea
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• v.26 no.1
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• pp.1-14
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• 2019

Large landslide is a type of mass movement that causes drastic landform changesin a short period, and it causes huge human and property damage over a large area. The purpose of this study is to categorize the types and characteristics of large landslides around the Kokomeren River basin, Kyrgyzstan and to discuss the geomorphic development after the large landslides. The topographic analysis about a total of 20 landslides documented collapsed volumes of 0.01 to 1.10 km³, height drops of 180 to 1,770 m, and runout distances of 1,200 to 5,400 m. Rock avalanche and rockslide are identified as major types of large-scale landslides in the study area. Rock avalanches can be divided into P-type, J-type, and S-type based on the features of slope failure and kinematic characteristics of rock debris. Landslide synchronistic landforms such as trimlines, transverse ridges, longitudinal ridges, levees, and hummocks are well developed in the rock avalanche. The pieces of evidence of landslide dam, landslide-dammed lake, and remnant outburst flood deposits are observed in the upstream and downstream where the rockslides occurred. The Ak-Kiol landslide dam is the best example of a geomorphic development due to lake spillover and the large landslides were likely to be triggered by huge paleo-seismic events.

• Journal of the Korean Geotechnical Society
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• v.30 no.6
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• pp.61-68
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• 2014

The main objective of this study is to evaluate the preliminary landslide hazard based on the identification of geomorphological features, which are believed to be critical values in the initial state of landslides. Two methods, SINMAP and Planarity analyses, are used to simulate those characteristics where landslides are actually located. Results showed that both methods well discriminate geomorphic features between stable and unstable domains in the landslide areas. SINMAP analysis which is the consecutive model considering external factors like infiltration identifies the landslide hazard especially for debris flow type landslides better than plararity analysis focusing on a specific area. This analysis combined with other methods dealing with specific characteristics of geomorphological feature, the accurate landslide hazard will be evaluated.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.67-81
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• 2020

The rapid climatic changes being caused by global warming are resulting in abnormal weather conditions worldwide, which in some regions have increased the frequency of landslides. This study was aimed to analyze and compare the landslide susceptibility using the Frequency Ratio (FR), Statistical Index, Weight of Evidence, Certainty Factor, and Index of Entropy (IoE) at Woomyeon Mountain in South Korea. Through the construction of a landslide inventory map, 164 landslide locations in total were found, of which 50 (30%) were reserved to validate the model after 114 (70%) had been chosen at random for model training. The sixteen landslide conditioning factors related to topography, hydrology, pedology, and forestry factors were considered. The results were evaluated and compared using relative operating characteristic curve and the statistical indexes. From the analysis, it was shown that the FR and IoE models were better than the other models. The FR model, with a prediction rate of 0.805, performed slightly better than the IoE model with a prediction rate of 0.798. These models had the same sensitivity values of 0.940. The IoE model gave a specific value of 0.329 and an accuracy value of 0.710, which outperforms the FR model which gave 0.276 and 0.680, respectively, to predict the spatial landslide in the study area. The generated landslide susceptibility maps can be useful for disaster and land use planning.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.1 s.39
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• pp.39-46
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• 2007

Most areas in Kangwon Province are mountainous and vulnerable to landslide due to the rainy season in summer and the localized torrential downpour triggered by abnormal climate. In particular, the rainfall is one of direct reasons for landslide. In accordance with the analysis of the relevance between the landslide areas and the accumulated rainfall for four months, there are severe damages of landslide to the areas having more than 1,100 mm of rainfall during three(3) months. Further, it indicates that the more the accumulated rainfall is the greater the size of landslide. These analyses show that the rainfall causes the possible and potential landslide in the vulnerable areas. And also, it means that there exist strong possibilities of landslide even in the areas of lower vulnerability if the amount of rainfall is above certain standard level. Accordingly, in this study we stored the GIS database on the causes and factors of landslide in the southern parts of Kangwon province and conducted simulations on the change of distribution of vulnerable areas by varying the rainfall conditions and by using the evaluation data of landslide vulnerability. As such a result, we found that the landslide could potentially occur if the amount of rainfall is 200 mm and more.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.185-190
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• 2005

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. In order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The six landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The six factors consist of two topographic factors and four geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 86.5% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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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

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.444-455
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• 2009

Great concerns on geotechnical risk & hazard assessment have been increased due to human and economic damage by natural disasters with recent global climate changes. In this paper, geotechnical problems in particular, landslides which is interested in European countries and North America, were mainly discussed. For these, 18 key topics on geotechnical risk and hazards which had been discussed at the LARAM 2008 workshop in Italy were analyzed after grouping by subjects. Main topic contents consisted of applications such as field measurement, early warning systems, uncertainty analysis of parameters using radar, optical data and statistical theory and so on. And the problems related to analysis of vulnerability and deformation due to earthquakes, investigation of gas zone using seismic reflection data in a landslide area, risk quantification and hazard assessment of landslide movements and multi-dimensional analysis for stability of complex slopes were attracted. Also, there were studies on risk matters of cultural heritage, the blockglide of clayey ground, simulations of debris flows based on GIS, quantification of the failure processes of rock slopes, a meshless method for 3D crack modelling, and finally risk assessment for cryological processes due to global warming.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.3
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• The Journal of Engineering Geology
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• v.29 no.4
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• pp.541-552
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• 2019

In this study, landslide flume tests were performed to analyze characteristics of ground characteristics and landslide occurrence due to rainfall infiltration. As test materials, weathered granite soil and gneiss soil, the most frequent landslides in Korea, were used, and landslides were triggered by heavy rain (Intensity = 200 mm/hr). The measurement sensors were installed with 3 sets at toe, slope, top part and shallow (GL-0.2 m), middle (GL-0.4 m), and deep (GL-0.6 m) depth in the slope and measured at 10 second intervals. After landslide flume tests, the slope stability analysis was performed by applying the unsaturated soil theory based on the change of ground characteristics and compared with actual landslide occurrence from flume test. As a result of the analysis, factor of safety reflected the landslide occurrence from flume test and factor of safety decreased as rainfall infiltration, leading to slope failure. Finally we compared to the factor of safety below 1 and actual landslide occurrence time, the average difference was 1,600 seconds for weathered granite soil and 5,400 seconds for weathered gneiss soil.