• Geomechanics and Engineering
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• v.28 no.3
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• pp.283-298
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• 2022

Landslides triggered by the combination of heavy precipitation and anthropological disturbance in hilly areas cause severe damage to human lives, properties, and infrastructure constructions. A comprehensive investigation of the influencing factors and failure mechanisms of landslides are significant for disaster mitigation and prevention. This paper utilized the combination of detailed geological investigation, physical experimental testing as well as numerical modelling to determine the failure mechanism, and proposed a countermeasures of the Lantian landslide occurred on 2, July 2017. The results reveal that the Lantian landslide is a catastrophic reactivated slide which occurred in an active tectonic region in Southwest China. Because of the unique geological settings, the fully to highly weathered basalts in the study area with well-developed fractures favored the rainwater infiltration, which is the beneficial to slide reactivation. Engineering excavation and heavy precipitation are the main triggering factors to activate the slide motion. Two failure stages have been identified in the landslide. The first phase involves a shallow mass collapse originated at the upper slopes, which extends from the road to platform at rear part, which is triggered by excavation in the landslide region. Subjected to the following prolonged rainfall from 19 June to 2 July, 2017, the pore water pressure of the slope continually increased, and the groundwater table successively rise, resulting in a significant decrease of soil strength which leads to successive large-scale deep slide. Thereinto, the shallow collapse played a significant role in the formation of the deep slide. Based on the formation mechanisms of the landslide, detailed engineering mitigation measures, involving slope cutting, anchor cable frame, shotcrete and anchorage, retaining wall and intercepting ditch were suggested to reduce the future failure risk of the landslide.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.673-687
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• 2023

Exploratory data analysis is the process of observing and understanding data collected from various sources to identify their distributions and correlations through their structures and characterization. This process can be used to identify correlations among conditioning factors and select the most effective factors for analysis. This can help the assessment of landslide susceptibility, because landslides are usually triggered by multiple factors, and the impacts of these factors vary by region. This study compared two stages of exploratory data analysis to examine the impact of the data exploration procedure on the landslide prediction model's performance with respect to factor selection. Deep-learning-based landslide susceptibility analysis used either a combinations of selected factors or all 23 factors. During the data exploration phase, we used a Pearson correlation coefficient heat map and a histogram of random forest feature importance. We then assessed the accuracy of our deep-learning-based analysis of landslide susceptibility using a confusion matrix. Finally, a landslide susceptibility map was generated using the landslide susceptibility index derived from the proposed analysis. The analysis revealed that using all 23 factors resulted in low accuracy (55.90%), but using the 13 factors selected in one step of exploration improved the accuracy to 81.25%. This was further improved to 92.80% using only the nine conditioning factors selected during both steps of the data exploration. Therefore, exploratory data analysis selected the conditioning factors most suitable for landslide susceptibility analysis and thereby improving the performance of the analysis.

• 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.

• Journal of Korean Society of Forest Science
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• v.108 no.2
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• pp.216-223
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• 2019

This study was conducted to measure the changes in the geological and soil properties following slow-moving landslide events in Yangbuk-myun and Gyungju-si, Gyeongsangbuk-do, South Korea. The geological characteristics of the study site comprised black shale in the Gyeongsang nodal group formed in the Cretaceous period and quartz feldspar carcinoma in the east side with conglomerate in the Yeonil group formed in the Quaternary period. The study site exhibited the geologic characteristics of a slow-moving landslide with severely weathered rocks. The maximum collapsing depth of the slow-moving landslide was 12.0 m with colluvial deposits. The strike and joint aspects in the slope areas of the slow-moving landslides were $N46^{\circ}E$ in lower slope and $N62^{\circ}E$ in upper slope, respectively. Soil hardness of ${\leq}20cm$ deep was not measured because of the completely disturbed soil resulting from soil creeping. Soil from 25 to 90 cm deep was 1.4-4.7 times softer in the slow-moving landslide areas than in the undisturbed or natural forests. Soil bulk density was $1.24-1.29g/cm^3$ in land creep areas. Soil bulk in both areas was 1.6 times denser than that in the natural forest. The soil pore space was 51.5-53.3% in the land creep areas. The values are 1.3-1.4 times lower than those within the natural forest. Black shale areas showed the lowest coefficient of permeability (8.75 E-06 cm/s) and mesopore ratio (pF 2.7: 9.8%) compared with those resulting from other study areas.

• 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.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1251-1258
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• 2008

The purpose of this research is to introduce the new temporary earth retaining wall system using landslide stabilizing piles. This system is a self-supported retaining wall(SSR) without installing supports such as tiebacks, struts and rakers. The SSR is a kind of gravity structures consisting of twin parallel lines of piles driven below dredge level, tied together at head of soldier piles and landslide stabilizing piles by beams. There are three types of excavation wall structures: standard method for medium retained heights(<8.0m), internal excavation method and slope excavation method for deep-excavation applications(>8.0m). In the present study, the measured data from seven different sites which the SSR was used for excavation were collected and analyzed to investigate the characteristic behavior lateral wall movements associated with urban excavations in Korea.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.162-170
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• 2018

The purpose of this study is to understand the ground change of large scale mountainous region and to estimate the active weak zone using geophysical exploration (electrical resistivity and refraction seismic explorations) in large scale deep landslide area located in Wanjugun, Jeollabukdo. We also analyzed the characteristics of deep landslides occurred in metamorphic rocks region and confirmed the approximate scale. As a result of comparative analysis of N-value by standard penetration test (SPT), low resistivity anomaly, and tension crack identified from field investigation, a discontinuity in soil layer was estimated at 10 ~ 15 m below the surface. Based on this results, the distribution pattern of active weak zone was confirmed between the discontinuity in soil layer and estimation line of bedrock.

• Journal of Korean Society of Forest Science
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• v.77 no.3
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• pp.276-282
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• 1988

Many landslides occurred at the western part of Gyeongnam province by the typhoon No. 875. Their conditions and causes were investigated and were summarized as follows : The total number of landslide occurred was 2,490 and its area was 156.53ha. In about 94% of landslides and about 97% of landslides area occurred in 3 counties, Sancheong, Hamyang and Geochang. The landslides smaller than 0.01ha was 49% of the total indicating that about half of them were the small landslides. Considering homogenous topography amount of precipitation and forest type landslides appeared to be mainly has a high affected by the geological factor because the landslides mainly occurred in the deep weathered soil of igneous rock. The landslides occured on concave slopes of 31 to $35^{\circ}$ in steepness with low crown density. In the area of the deep weathered soil, landslide likely occur repeatedly. Therefore, regular erosion control works are recommended in the area of pos for disaster prevention and counter-measures.

• The Journal of Engineering Geology
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• v.27 no.4
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• pp.475-487
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• 2017

We performed landslide flume tests to analyze characteristics of landslide occurrence and change in the ground materials due to rainfall infiltration. The test apparatus is composed of flume, rainfall simulator, and measurement sensors and landslides were triggered by heavy rainfall (Intensity=200 mm/hr) sprinkled at the above of an artificial slope. The measurement sensors for matric suction and volumetric water content were installed with 3 sets at shallow (GL-0.2 m), middle (GL-0.4 m), and deep depth (GL-0.6 m) in the slope and the tests were performed with in-situ, loose, and dense condition of each weathered soils of granite, gneiss, and mudstone. The analyses show that surface erosion was dominant in initial time of the test due to heavy rainfall and then landslides occur following locally happened transverse tension cracks. The characteristics of landslide were both shallow failure because of a spread of wetting front induced by the rainfall infiltration and retrogressive failure. While the matric suction was decreased rapidly without any precursor in the soil saturation, the volumetric water content was increased gradually, reached its maximum value, and then decreased rapidly with landslide.