• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• Journal of the Korean Geotechnical Society
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• v.21 no.8
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• pp.45-53
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• 2005

Shallow slope failures in residual soil during periods of prolonged infiltration are common over the world. Therefore, this study examines an approximate method to estimate the influence of infiltration on surficial stability of slopes by one-dimensional infiltration model. Modified GAML model based on the Green-Ampt model was extended to predict the infiltration behavior of two-layered slope. Then, the model has been considered to evaluate the likelihood of shallow slope failure which is induced by a particular rainfall event that accounts for the rainfall intensity and duration for various return periods in two-layered soil profile. The results obtained from the approximate method were compared with those obtained from numerical analyses. According to the results, with the use of properly estimated input parameters, the proposed method was found to give good results that agree reasonably well to those of the more rigorous finite element analyses.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.207-223
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• 2009

The TOPMODEL Topographic Index (TI) is widely used to predict the spatial distribution of soil moisture contents, The TI is one of terrain indices which are frequently used in spatially distributed environmental modelings. There have been studies on the evaluation and improvement of the TI. Most of them. however, have focused on only the modified multiple flow direction algorithm and algorithms for slope calculation have been paid little attention, In this research, we attempted to improve the TI by utilizing the infinitive flow direction (Dinf) algorithm and Horn slope algorithm. Then we attempt to analyze and evaluate the influence of the improved TI on hydrological responses of the TOPMODEL As a result. our approaching using the infinitive flow direction (Dinf) and Horn slope algorithm made the TI better than the multiple flow direction (MD8) - the multiple descent slope (MDS) algorithm. However, the model efficiency of discharges at the outlet was not increased. Our research may provide an insight to choose appropriate algorithms for calculating flow direction and slope in spatially distributed environmental modelings.

• Journal of the Society of Disaster Information
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• v.3 no.2
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• pp.147-169
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• 2007

This study investigates the reinforcing effects of the Multi-bar Spring nails with respect to the conventional Soil-nails in artificial slopes. Based on wide experience related to design and construction, soil nails have been widely applied to reinforce slope in the world. Multi-bar spring nails are one of the improved soil nailing methods. These method maximizes bending, shearing, pull-out resistance for those multi-nails, not unit nail, that are inserted in the borehole using special spacer at regular intervals. In addition, because cutting plane is confined effect resulting from a pressured plate at the end of the nails with compression spring equipment, slope stability is secured using MS-nailing method. Analyzing bending, pull-out, shearing condition of MS-nail, it was examined throughly elastic region, load transfer capacity, reinforcing effect on cutting plate of MS-nails. In addition, Pilot and laboratory tests, numerical analysis were carried out to verify the superiority of MS-nailing method. In case, MS nailing method is applied to reinforce artificial slope, it was analyzed that bending, pull-out, shearing resistance was increased more than existing nailing method was applied. In this study, it was shown that surface failure was more or less prevented using MS-nailing method, confining effect on cutting plane using spring stuck to flexible equipment.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.649-654
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• 2005

Shallow slope failures in residual soil during periods of prolonged infiltration are common over the world. One of the key factors that dominate slope stability is hydrological response associated with infiltration. Hence, the soil-water profile during rainfall infiltration into unsaturated soil must me examined to evaluate slope stability. However, the hydraulic response of unsaturated soil is complicated by inherent uncertainties of the soil hydraulic properties. This study presents a methodology for assessing the effects of parameter uncertainty of hydraulic properties on the response of a analytical infiltration model using first-order reliability method. The unsaturated soil properties are considered as uncertain variables with means, standard deviations, and marginal probability distributions. Sensitivities of the probabilistic outcome to the basic uncertainties in the input random variables are provided through importance factors.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.171-178
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• 2005

It is unavoidable to be formed slopes under special circumstance of Korea where 70% of the whole area are composed of mountains when civil engineering projects such as roads, site developments are increased with industrial development and horizontal expansions of urban area. Moreover, stability of the slopes become one of quite important issues under special meteorological characteristics that over two-thirds of annual average rainfall are concentrated in summer season and the localized torrential downpour are getting more frequent recently. Resulting in these circumstances, partial slope failures by debris flow of the high water content soils are occurred frequently in cutting soil slopes. In this case of debris flow slope failure, slope declination method are selected for their stable recovery because it is impossible to recover entirely by existing recovery methods. Seeding or special grass planting methods are followed separately without exception. The method by which entire recover with bigger stability ratio would be possible and grass planting work would be done simultaneously is developed. In this study, the results of the tests including a real construction history in a failed slope using developed method are described

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.67-75
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• 2004

The landslide is one of the most significant natural disasters, which cause a lot of loss of human lives and properties. The landslides in natural slopes generally occur by complicated problems such as soil properties, topography, and geology. Artificial Neural Network (ANN) model is efficient computing technique that is widely used to solve complicated problems in many research fields. In this paper, the ANN model with application of error back propagation method was proposed for estimation of landslide hazard in natural slope. This model can evaluate the possibility of landslide hazard with two different approaches: one considering only soil properties; the other considering soil properties, topography, and geology. In order to evaluate reasonably the landslide hazard, the SlideEval (Ver, 1.0) program was developed using the ANN model. The evaluation of slope stability using the ANN model shows a high accuracy. Especially, the prediction of landslides using the ANN model gives more stable and accurate results in the case of considering such factors as soil, topographic and geological properties together. As a result of comparison with the statistical analysis(Korea Institute of Geosciences and Mineral Resources, 2003), the analysis using the ANN model is approximately equal to the statistical analysis. Therefore, the SlideEval (Ver. 1.0) program using ANN model can predict landslides hazard and estimate the slope stability.

• 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 Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.517-522
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• 2003

Exact estimation of evapotranspiration is important to understand natural phenomena and social issues associated with the climate such as irrigation scheme, reservoir water management, and many other meteorological and climatological problems. To overcome limits of point measurement of evapotranspiration, several models have been developed through the techniques of remote sensing and Geographical Information System. SEBAL model is one of them, based on the energy balance equation, and it has a lot of advantages such as that it requires relatively small empirical relations. In this study, the SEBAL model has been calibrated and validated in Geumgang upper basin, Bochung-stream basin, Korea with 5 satellite images Landsat 5 TM. In validation, the results of SEBAL model were compared with those by Merton method. After validation, the spatial and temporal characteristics of the distribution of evapotranspiration within the basin were analyzed with 3 factors, the aspect of slope, the angle of slope, and the land cover.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.793-802
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• 2012

One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.