• Journal of Korean Society of Forest Science
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• v.103 no.2
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• pp.218-225
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• 2014

Landslides, one of earth's natural disasters, increase every year due to heavy rainfall, and cause damage to human life and assets. This study used the SHALSTAB to predict places at risk of landslides, in accordance with the intensity of rainfall. The parameter value of transmissivity was $19.58m^2/day$, the internal friction angle $36.3^{\circ}$, and the saturated unit weight $2.03t/m^3$. The slope stability status was classified into four categories, namely: unconditionally stable, stable, unstable and unconditionally unstable. In order to evaluate the applicability of the SHALSTAB, actual landslide areas were checked, with the unstable area under 263 mm rainfall. 85.1% of them were consistent. And so we can identify the distribution of places at risk of landslides, on the basis of the intensity of rainfall by means of SHALSTAB.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.1
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• pp.29-35
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• 1993

The vegetation such as grass, shrub, tree has been used to control the erosion and stabilize the slope for a long time. But the effects of vegetation on slope area is usually neglected in traditional stability analyses. There are many errors in slope analyses in thin soil mantles. Therefore the effects of vegetation is an important factor. But it is difficult and complex to represent the vegetation influence quantitatively in stability analysis. In this study, authors choose the landslide region at the Kum sung dong Kum-jung ku Pusan as a model area. Authors analyzed the degree of slope with the aerial photo interpretation and DTM data extracted from the topographic map, and the relationship of D.B.H. (diameter of breast height), height, and age of tree in field investigation data. Finally authors know the fact that landslide take place approximately 10 or 20 years later in arbitrary afforestable area where the degree of slope is 27. The prevention effect must be considered in the control of vegetation.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.202-202
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• 2016

Despite the potentially major influence of rainstorm patterns on the prediction of shallow landslides, this relationship has not yet received significant attention. In this study, five typical temporal rainstorm patterns with the same cumulative amount and intensity components comprising Advanced (A1 and A2), Centralized (C), and Delayed (D1 and D2) were designed based on a historical rainstorm event occurred in 2006 in Mt. Jinbu area. The patterns were incorporated as the hydrological conditions into the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model (TRIGRS), in order to assess their influences on pore pressure variation and changes in the stability of the covering soil layer in the study area. The results revealed that not only the cumulative rainfall thresholds necessary to initiate landslides, but also the rate at which the factor of safety (FS) decreases and the time required to reach the critical state, are governed by rainstorm pattern. The sooner the peak rainfall intensity occurs, the smaller the cumulative rainfall threshold, and the shorter the time until landslide occurrence. Left-skewed rainfall patterns were found to have a greater effect on landslide initiation. More specifically, among the five different patterns, the Advanced storm pattern (A1) produced the most critical state, as it resulted in the highest pore pressure across the entire area for the shortest duration; the severity of response was then followed by patterns A2, C, D1, and D2. Thus, it can be concluded that rainfall patterns have a significant effect on the cumulative rainfall threshold, the build-up of pore pressure, and the occurrence of shallow landslides, both in space and time.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.281-288
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• 2009

The purpose of this paper is to provide the statistical models for landslide prediction through quantification and AHP methods. Quantification method is a statistical method of providing quantity to qualitative variables by analyzing the observed data. In this paper, we suggest the quantification process based on the results of cannonical correlation analysis. In contrast with the quantification method which is based on given data the AHP(Analytic Hierarchy Process) technique is a kind of method based on questionaire data which is usually taken from professionals. We analyze both the real data(provided from KIGAM) and questionaire data collected from professionals of various related area. We developed two kinds of evaluation table which provide the scores of land slide possibility and the logistic model providing the probability of occurring landslide. Finally we compare the performance and evaluate the stability of the suggested two models.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.619-620
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• 2012

This paper proposes a model of the real time monitoring system based on Ubiquitous Sensor Network (USN) for the detection and prediction of landslides. For this purpose, the real time monitoring system with tilting sensor and USN was set up and the performance was conducted. The performance was accomplished by conducting both field examinations and the experimental evaluation of the monitoring system. The results of this study show that the movements detected by the sensor module coincide with the actual displacement of field and the data measured from the sensor modules through USN transfer to the monitoring system without errors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3628-3633
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• 2012

This paper proposes a model of the real time monitoring system based on Ubiquitous Sensor Network (USN) for the detection and prediction of landslides. For this purpose, the real time monitoring system with tilting sensor and USN was set up and the performance was conducted. The performance was accomplished by conducting both field examinations and the experimental evaluation of the monitoring system. The results of this study show that the angle $0^{\circ}$, $-10^{\circ}$, $-20^{\circ}$ and $0{\sim}-30^{\circ}$ of sensor position detected by the sensor module coincide with the data measured from USN monitoring system by giving a sampling time 100[msec]. Consequently, the proposed model of the real time monitoring system with tilting sensor based on USN will be widely used as a monitoring system in the exposure to dangerous landslide regions.

• The Journal of Engineering Geology
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• v.18 no.3
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• pp.303-309
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• 2008

A probability of slope hazards was predicted at a natural terrain around the stone relics of Jinjeon-saji area, which is located in Yangyang, Kangwon Province. As the analyzing results of field investigation, laboratory test and geology and geomorphology data, the effect factors of landslides occurrence were evaluated. Also, the landslides prediction map was made up using the prediction model by the effect factors. The landslide susceptibility of stone relics was investigated as the grading classification of occurrence probability. In the landslides prediction map, the high probability area was $3,489m^2$ and it was 10.1% of total prediction area. The high probability area has over 70% of occurrence probability. If landslides are occurred at the predicted area, the three stories stone pagoda of Jinjeon-saji(National treasure No. 122) and the stone lantern of Jinjeon-saji(Treasure No.439) will be collapsed by debris flow.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.515-525
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• 2014

Recently, because of increasing in downpour and typhoon, which are caused by climate changes, those sedimentation disasters, such as landslide and debris flow, have become frequent. Those sedimentation disasters take place in natural slope. In order to predict debris flow damage range within wide area, the response model is more appropriate than numerical analysis. However, to make a prediction using Random Walk Model, the regional parameters is needed to be decided, since the regional environments conditions are not always same. This random Walk Model is a probability model with easy calculation method, and simplified slope factor. The objective of this study is to calculate the optimal parameters of Random Walk Model for Umyeon mountain in Seoul, where the large debris flow has occurred in 2011. Debris flow initiation zones and sedimentation zones were extracted through field survey, aerial photograph and visual reading of debris flow before and after its occurrence via LiDAR DEM.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.637-646
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• 2020

The shallow landslide-trigerred debris flow in hillslope catchments is the primary geological phenomenon that drives landscape changes and therefore imposes risks as a natural hazard. In particular, debris flows occurring in urban areas can result to substantial damages to properties and human injuries during the flow and sediment transport process. To alleviate the damages as a result of these debris flow, analytical models for flow and damage prediction are of significant importance. However, the analysis of debris flow model parameters is not yet sufficient, and the analysis of the entrainment, which has a significant influence on the flow process and the damage extent, is still incomplete. In this study, the effects of erosion and erosion process on the flow and the impact area due to the change in the soil parameters are analyzed using Deb2D model, a flow analysis model of debris developed in Korea. The research is conducted for the case of the Mt. Umyeon landslide in 2011. The resulting impacted area, total debris-flow volume, maximum velocity and inundated depth from the Erosion model are compared to the field survey data. Also, the effect of the entrainment changing parameters is analyzed through the erosion shape and depth. The debris flow simulation for the Raemian and Shindong apartment catchment with the consideration of entrainment effect and erosion has been successful. Each parameter sensitivity could be analyzed through sensitivity analysis for the two basins based on the change in parameters, which indicates the necessity of parameter estimation.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.33-33
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• 2016

산사태 발생 예측은 재해를 예방하고 대처하기 위한 가장 근본적이며 효과적인 방법이나, 과학기술의 발전과 많은 노력에도 불구하고 아직 산사태의 발생 장소와 시기를 예측하는 것은 매우 어려운 일이다. 산사태 발생 예측 기법은 크게 경험론적 지수기법, 통계적 해석기법, 물리적 해석 기법으로 나뉠 수 있다. 이 세 방법은 각기 장단점이 있으나 일반적으로 후자로 갈수록 많은 데이터가 요구되고, 해석에 시간이 필요하며, 보다 신뢰할만한 결과를 도출할 수 있다. 경험론적 지수 기법은 국내에서 실무적으로 널리 활용되고 있으며, 통계적 해석기법에 관한 연구도 수행된 바 있다. 하지만 이 두 방법론은 일정량 또는 일정강도 이상의 강우 발생 시 산사태의 발생 위험도를 공간적으로 예측할 수 있으나, 산사태의 발생 시점과 연속적인 강우량 또는 강우강도의 관계를 정량적으로 분석하기 힘든 한계가 있어 최근에는 이러한 한계를 극복하기 위해 최근 무한사면안정 모형과 토양수분침투 모형을 결합한 시변 사면안정모형들이 활용되기 시작하고 있다. 대표적으로는 TRIGRS가 있으며, 이 모형에서는 선형화한 1차원 Richards 방정식의 해석해를 활용하여 토양수분량을 계산한 후 이 정보를 무한사면안정모형에 반영하여 시변적인 사면안정도를 구하고 있다. 하지만 Richards 방정식을 선형화하기 위해서 제한된 토양수분-압력 관계식이 사용되며, GUI가 제공되지 않아 전처리 및 후처리가 번거로운 한계가 있다. 본 연구에서는 이러한 한계를 개선하기 위해 3차원 Richards방정식을 수치적으로 계산하여 보다 다양한 토양수분-압력 모형과 초기조건을 반영할 수 있게 하였다. 또한 GUI를 지원하여 사용자가 보다 손쉽게 해석모형을 사용할 수 있도록 하였다.