• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5115-5122
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• 2013

This paper has studied about the development and application of landslide collapse prediction real-time monitoring system based on USN to detect and measure the collapse of landslide. The rainfall measuring sensor, gap water pressure sensor, indicator displacement measuring sensor, index inclination sensor, water content sensor and image analysis sensor are selected and these are applied on the test bed. Each sensor's operation and performance for reliability verification is tested by the instrument which is installed in the field. As the result, u-IT based real-time landslide monitoring system which is developed by this research for landslide collapse detection could minimize life and property damages because it makes advance evacuation with collapse risk pre-estimate through real-time monitoring on roadside cut and bedrock slopes. This system is based on the results of this study demonstrate the effect escarpment plan are spread throughout.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.313-318
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• 2006

The main cause of natural disaster in Korea is meteorological phenomenon, such as typhoon, heavy rain, storm, rainstorm, heavy snow, hailstorm, overflowing of sea and so on(including thunderstroke, blast, snow damage, freezing and earthquake), and among those disasters, heavy rain takes place most often, and it occupies 80% of total disaster Especially, disaster related to slope collapse (landslide, collapse of retaining wall, burying ect.) takes place every year due to meteorological cause such as localized heavy rain, which is getting stronger. (National Institute for Prevention Disaster, 2002, Meteorological Administration) Accordingly, it is necessary to analyze the features of slope collapse related to natural disaster in Korea, and also to make up counterplan to prevent disaster. This paper will try to analyze potential areas which are susceptible to landslide regarding factors inducing landslide and heavy rain, and to evaluate the potentiality of landslide regarding local particularity of rainfall, furthermore to provide essential information for development of community such as preventing damages from landslide, construction Industry, and effective use of land.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1260-1265
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• 2009

Topographical features in South Korea is characterized that 70% of territory is composed of the mountains that can experience intense rainfall during storms in the summer and autumn. Efficient planning and management of landscape becomes utmost important since the cutting slopes in the mountain areas have been increased due to the limited construction areas for the roadway and residential development. This paper proposed an efficient way of slope management for the landslide risk by developing Web-GIS landslide risk management system. By deploying the Logistic Regression Analysis, the system could increase the prediction accuracy that the landslide disaster might be occurred. High resolution survey technology using GPS and Total-Station could extract the exact position and visual shape of the slopes that accurately describe the slope information. Through the proposed system, the prediction of damage areas from the landslide could also make it easy to efficiently identify the level of landslide risks via web-based user interface. It is expected that the proposed landslide risk management system can support the decision making framework during the identification, prediction, and management of the landslide risks.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.131-136
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• 2003

Landslide is a natural disaster frequently noticed In korea during monsoon season in flicting nationwise damages on human lives, properties, transportation networks, construction sites, etc. This study is about landslide characteristic in rainfall. This study selects seven sites that occured in 2001 and 2002. So elect areas divide and studied special quality by carcinoma by igneous rock, metamorphic rock, sedimentary rock. According to study finding, because igneous rock area is very thin into 1m interior and exterior soil layer, failures happened much rock and soil interface. There was place that depth of soil layer becomes about 2∼3m being area that receive serious weathering case of metamorphic rock. Therefore, at collapse much debriflow occurrence expect. Case that sedimentary rock area is broken through stratification looked. When see such results, it may become many helps to study characteristics of landslide occurrence area grasping collapse special quality by rock type.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.439-447
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• 2019

In this study, experiments were conducted to establish appropriate measures for slopes with high risk of collapse and to obtain results for minimizing slope collapse damage by detecting the micro-displacement of soil in advance by installing a laser sensor and a vibration sensor in the landslide reduction model experiment. Also, the behavior characteristics of the soil layer due to rainfall and moisture ratio changes such as pore water pressure and moisture were analyzed through a landslide reduction model experiment. The artificial slope was created using granite weathering soil, and the resulting water ratio(water pressure, water) changes were measured at different rainfall conditions of 200mm/hr and 400mm/hr. Laser sensors and vibration sensors were applied to analyze the surface displacement, and the displacement time were compared with each other by video analysis. Experiments have shown that higher rainfall intensity takes shorter time to reach the limit, and increase in the pore water pressure takes shorter time as well. Although the landslide model test does not fully reflect the site conditions, measurements of the time of detection of displacement generation using vibration sensors show that the timing of collapse is faster than the method using laser sensors. If ground displacement measurements using sensors are continuously carried out in preparation for landslides, it is considered highly likely to be utilized as basic data for predicting slope collapse, reducing damage, and activating the measurement industry.

• 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.

• Journal of the Korean GEO-environmental Society
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• v.12 no.8
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• pp.5-12
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• 2011

This study was performed to analyze the degree of rainfalls, the duration time of rainfalls, the inclination of slopes and other damage causes depending on the ground condition, when the landslide occurs by the rainfall. Based on that, a big and a small model soil box were compared to examine the features of landslides, which is ultimately for forecasting landslides. An artificial rainfall device was installed in the model box, and the large model box has a real-size slope in it. Also, various measures were fulfilled such as collapse forms, a pore pressure, an earth pressure and moisture contents in order to analyze the effect of the model box size on the landslide mechanism and to test the usability of a small model box as a material for landslide experiments.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.61-69
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• 2010

The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.197-205
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• 2016

Rainfall-induced landslide disaster case histories are typically required to establish critical lines based on the decrease coefficient for judging the likelihood of slope collapse or failure; however, reliably setting critical lines is difficult because the number of nationwide disaster case histories is insufficient and not well distributed across the region. In this study, we propose a method for setting the critical area to judge the risk of slope collapse without disaster case history information. Past 10 years rainfall data based on decrease coefficient are plotted as points, and a reference line is established by connecting the outermost points. When realtime working rainfall cross the reference line, warning system is operating and this system can be utilized nationwide through setting of reference line for each AWS (Automatic Weather Station). Warnings were effectively predicted at 10 of the sites, and warnings could have been issued 30 min prior to the landslide movement at eight of the sites. These results indicate a reliability of about 67%. To more fully utilize this model, it is necessary to establish nationwide rainfall databases and conduct further studies to develop regional critical areas for landslide disaster prevention.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.4
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• pp.219-227
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• 2014

Natural disasters such as a ground collapse and a landslide have broken out due to the climate change of the Korea and the reckless expansion of cities and roads. The climate changes and the reckless urbanization have made the ground weak. Thus, it is important to keep a close eye on the highly weakened landslide and to prevent its natural disasters. In order to prevent these disasters, this paper presents a system of recognizing the road slide condition by measuring the displacements using laser scanner instrument. The previous system of monitoring the road slide has some problems as inaccurate recognition due to using only images from a camera, or expensive system such as artificial satellites and aircraft systems. To solve this problem, our proposed system uses the 3D range data from the laser scanner for measuring the accurate displacement of the road slide and optical flows from the Lucas-Kanade algorithm for recognizing the road slide in the image.