• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.737-741
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• 2012

본 연구에서는 2011년 7월 27일 집중호우로 인한 서울시 우면산 산사태 지역을 대상으로 뿌리의 보강효과와 분포형 습윤지수를 고려한 GIS기반의 무한사면안 해석기법을 이용하여 사면안정해석을 실시하였다. 사면안정해석을 위한 지형 지질학적 매개변수는 수치지도, 정밀토양도 및 임상도(임상도와 영급도)로부터 추출하여 $10m{\times}10m$ 해상도의 공간분 포형 데이터베이스로 변환하였다. 또한, 분포형 습윤지수의 산정을 위한 비집수면적(specific catchment area)은 무한방향흐름 기법(IFD, infinity flow direction)을 이용하여 결정하였으며, 모형의 입력 강우자료는 서울시 서초와 남현 AWS의 산사태 발생초기와 종기시의 평균 일강우량을 적용하였다. 대상유역의 사면안정해석을 위해 격자별 안전률은 4개의 등급(unstable, quasi stable, moderately stable, stable)으로 구분하여 도시하였다. 산사태 발생인자별 분석결과, 무한사면안정해석기법을 이용하여 산정된 사면안전률은 사면경사에 매우 민감하게 반응하는 것으로 분석되었으며, 거주지 주변의 절개지 부근과 산지정상부근의 급경사지에서 불안정 지역이 집중적으로 분포하고 있음을 확인하였다.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.

• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.171-179
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• 2015

The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS, UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.687-699
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• 2018

Understanding rain infiltration into the ground is an important feature of landslide risk evaluation. In this study, a landslide risk index for the study area is suggested, wherein the result of the landslide risk evaluation, based on the factor of safety (FS), is used. The landslide risk index is a landslide risk prediction index that utilizes the saturated depth ratio of the ground. Based on the landslide risk result for the study area, it was found that the FS was first to decrease. However, it gradually became convergent over the 50-year rainfall intensity study period, a result that is similar to the relationship between the saturated depth ratio and soil thickness. Moreover, saturated depth was also found to be deeper on gentle slopes than steep slopes. As such, the landslide risk index, based on the Inhu-ri study result, is thus suggested. Additionally, the suggested landslide risk index was compared and analyzed against the rainfall intensity of previous landslide experience. Results thus revealed that almost all landslides that occurred were over 0.7, which is the second grade, based on the landslide risk index.