• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.17-23
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• 2003

In Korea terrestrial fluvial sequences can be used as pedological and sedimentological markers indicating a millenium-scale environmental and climatic changes imprinted in fluvial sub-environments, which in turn are represented by the cyclicity of fluvial sands, backswamp organic muds, and flooding muds intercalations of frostcracked or dessicated brown paleosols. Post LGM and Holocene fluvial and alluvial sedimentary sequences of Korea are formed in such landscapes of coastal, floodplain, backswamp and hillslope areas. Among them, the most outstanding depositional sequences are fluvial gravels, sands and organic mud deposits in coastal, fluvial, or alluvial wetlands. The aim of this study is to explain the sedimentary sequences and palynofloral zones since the last 15,000years, on the basis of organic muds layers intercalated in fluvial sand deposits. Jangheung-ri site of Nam river, Soro-ri site of Miho river, Youngsan rivermouth site in Muan, Oksan-ri site of Hampyeong and Sanggap-ri site of Gochang are illustrated to interpret their sedimentary facies, radiocarbon datings, and palynofloral zonation. Up to the Middle to Late Last Glacial(up to 30-35Ka), old river-bed, flooding, and backswamp sequences contain such arboreal pollens as Pinus, Abies, and Picea, and rich in non-arboreal pollens like Cyperaceae, Gramineae, Ranunculaceae, and Compositae. During the LGM and post-LGM periods until Younger Dryas, vegetation has changes from the sub-alpine conifer forest(up to about 17-11Ka), through the conifer and broad-leaved deciduous forest, or mixed forest (formed during 16,680-13,010yrB.P), to the deciduous and broad-leaved forest (older than 9,500yrB.P). In the Earliest Holocene flooding deposits, fragments of plant roots are abundant and subjected to intensive pedogenic processes. During Holocene, three arboreal pollen zones are identified in the ascending order of strata； Pinus-Colyus zone(mixed conifer and deciduous broad-leaved forest, about up to 10Ka), Alnus-Quercus forest (the cool temperate deciduous broad-leaved forest, about 10Ka-2Ka), and Pinus forest (the conifer forest, about after 2Ka), as examplified in Soro-ri site of Cheonwon county. The palynological zonations of Soro-ri, Oksan-ri, Sanggap-ri, Youngsan estuary, and Gimhae fluvial plain have been recognized as a provisional correlation tool, and zonations based on fluvial backswamp and flooding deposits shows a similar result with those of previous researchers.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.202-205
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• 2006

The objective of this study is to analyze the hazard-areas for landslide using GIS and RS. LRA (Logistic Regression Analysis) and AHP (Analytic Hierarchy Program) methods were used for evaluation of the hazard-areas by six topographic factors (slope, aspect, elevation, soil drain, soil depth, land use). These methods were applied to Anseong-si where frequent landslides were occurred mainly by the regional heavy rainfall. A landslide hazard-map of Anseong-si could describe into 7 hazard-grades. As results, LRA method was underestimated in higher grades areas, while AHP method was underestimated in lower grades areas. In order to evaluate the hazard-areas for landslides with accuracy, these results of each method were overlapped and the results of suggested method were compared with the historical landslide hazard records of KFRI (Korea Forest Research Institute).

• Steel and Composite Structures
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• v.47 no.4
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• pp.451-454
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• 2023

Landslides are one of the natural disasters that cause a lot of financial and human losses every year It will be all over the world. China, especially. The Mainland China can be divided into 12 zones, including 4 high susceptibility zones, 7 medium susceptibility zones and 1 low susceptibility zone, according to landslide proneness. Climate and physiography are always at risk of landslides. The purpose of this research is to prepare a landslide hazard map using the Hierarchical Analysis Process method. In the GIS environment, it is in a part of China watershed. In order to prepare a landslide hazard map, first with Field studies, a distribution map of landslides in the area and then a map of factors affecting landslides were prepared. In the next stage, the factors are prioritized using expert opinion and hierarchical analysis process and nine factors including height, slope, slope direction, geological units, land use, distance from Waterway, distance from the road, distance from the fault and rainfall map were selected as effective factors. Then Landslide risk zoning in the region was done using the hierarchical analysis process model. The results showed that the three factors of geological units, distance from the road and slope are the most important have had an effect on the occurrence of landslides in the region, while the two factors of fault and rainfall have the least effect The landslide occurred in the region.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.2
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• pp.53-58
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• 1993

Landslides, failure of slope stability by natural or artificial factors, occur loss of life and properties. Recently, landslides hazard area predict statistical methods and field measurements, but there are so many difficulties to find the occurrence system because of its complexity. To predict the landslide harvard region, model area is the Seodong in Pusan where occurred landslides. Database of ground height made the each topography in map scale of 1 : 25,000, 1 : 10,000, 1 : 5,000 and 1 : 1,200. Authors knew to landslide hazard area by the weight of ground height data and slope angle data. Finally, aerial photo analysis is possible find landslide hazard area.

• Disaster Prevention Review
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• v.14 no.4
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• pp.118-119
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• 2012

• Disaster Prevention Review
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• v.15 no.1
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• pp.70-71
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• 2013

• Journal of the Korean Geotechnical Society
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• v.30 no.6
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• pp.61-68
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• 2014

The main objective of this study is to evaluate the preliminary landslide hazard based on the identification of geomorphological features, which are believed to be critical values in the initial state of landslides. Two methods, SINMAP and Planarity analyses, are used to simulate those characteristics where landslides are actually located. Results showed that both methods well discriminate geomorphic features between stable and unstable domains in the landslide areas. SINMAP analysis which is the consecutive model considering external factors like infiltration identifies the landslide hazard especially for debris flow type landslides better than plararity analysis focusing on a specific area. This analysis combined with other methods dealing with specific characteristics of geomorphological feature, the accurate landslide hazard will be evaluated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.211-218
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• 1993

Landslides, failure of slope stability by natural or artificial factors, occur loss of life and properties. Recently, statistical methods and field measurements are used to a study for prediction of landslide harzard area, but there are so many difficulties to find the occurence system because of its complexity. In this study, authors choose the model area where occured landslides to predict the landslide hazard. Authors made a database of ground height to compare the each topography by scale of 1 : 25,000, 1 : 10,000, 1 : 5,000 and 1 : 1,200. Authors predict to landslide hazard area by the weight of ground height data and slope angle data. Finally, authors could know the possibility of prediction to find the landslide hazard partly.

• Magazine of korean Tunnelling and Underground Space Association
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• v.22 no.1
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• pp.26-35
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• 2020

Tunnelling to bypass major landslide areas is considered as a good and long-term environmentally friendly solution to reduce an existing hazard. In Norway, hundreds of kilometres of tunnels have been constructed in areas prone to landslides and snow avalanches. Although tunnelling is considered as an expensive mitigation strategy for bypassing landslides, analysis indicate that in some cases the cost of building a tunnel can be repaid by savings in driving costs (fuel) alone over a period of 5-10 years due to reduced driving distances. The other benefits of constructing tunnels in landslide areas include savings in time and increased safety. The Norwegian Method of Tunnelling (NMT) is considered safe, efficient and cost effective compared to other tunnelling techniques. Some aspects of NMT, which are considered safe and cost efficient, are presented. The application of updated rock support techniques, including reinforced ribs of shotctrete (RRS), which is a key component of the Norwegian Method of Tunnelling (NMT), is highlighted.

• 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.