• Journal of the Korean Society of Safety
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• v.27 no.6
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• pp.172-177
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• 2012

In areas around Deoksan Li and Deokjeon Li, Inje Eup, Inje Gun, located between $38^{\circ}2^{\prime}55^{{\prime}{\prime}}N$ and $38^{\circ}5^{\prime}50^{{\prime}{\prime}}N$ in latitude and $128^{\circ}11^{\prime}20^{{\prime}{\prime}}E$ and $128^{\circ}18^{\prime}20^{{\prime}{\prime}}E$ in longitude, large-sized avalanche disasters occurred due to Typhoon Ewiniar in 2006. As a result, 29 people were dead or missing, along with a total of 37.25 billion won of financial loss(Gangwon Province, 2006). To evaluate such landslide and debris flow risk areas and their vulnerability, this study applied a technique called 'Weight of Evidence' based on GIS. Especially based on the overlay analysis of aerial images before the occurrence of landslides and debris flows in 2005 and after 2006, this study extracted 475 damage-occurrence areas in a shape of point, and established a DB by using such factors as topography, hydrologic, soil and forest physiognomy through GIS. For the prediction diagram of debris flow and landslide risk areas, this study calculated W+ and W-, the weighted values of each factor of Weight Evidence, while overlaying the weighted values of factors. Besides, the diagram showed about 76% in prediction accuracy, and it was also found to have a relatively high correlationship with the areas where such natural disasters actually occurred.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.103-114
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• 2017

The landslide disaster damage has been increased by mountain development, leading to construction of educational facilities, medical facilities, petty industrial facilities, and large housing complexes. Therefore, effective regulation is required as an effort in urban planning solutions. For suggesting specific mitigation strategies on urban landslide, this study aims to define evaluation criteria for urban planning management of debris-flow disaster. AHP (Analytic Hierarchy Process), one of the multiple criterion decision making methods, was utilized in this study. This study makes use of 16 sub-criteria under the framework of hazard, exposure, and vulnerability, and well-planned expert survey measures their weights. The weights are also applied to evaluate each grid in urban space (min $10{\times}10m$) and classify it with red, orange, yellow, or green grade so that areas at higher risk are clearly identified. This study concludes that the suggested method is useful to support a strategies for urban planning management of debris-flow disaster, particularly in a GIS base.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.5
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• pp.221-230
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• 2023

This study proposes a methodology for assessing seismic liquefaction hazard by implementing high-resolution three-dimensional (3D) ground models with high-density/high-precision site investigation data acquired in an area of interest, which would be linked to geotechnical numerical analysis tools. It is possible to estimate the vulnerability of earthquake-induced geotechnical phenomena (ground motion amplification, liquefaction, landslide, etc.) and their triggering complex disasters across an area for urban development with several stages of high-density datasets. In this study, the spatial-ground models for city development were built with a 3D high-precision grid of 5 m × 5 m × 1 m by applying geostatistic methods. Finally, after comparing each prediction error, the geotechnical model from the Gaussian sequential simulation is selected to assess earthquake-induced geotechnical hazards. In particular, with seven independent input earthquake motions, liquefaction analysis with finite element analyses and hazard mappings with LPI and LSN are performed reliably based on the spatial geotechnical models in the study area. Furthermore, various phenomena and parameters, including settlement in the city planning area, are assessed in terms of geotechnical vulnerability also based on the high-resolution spatial-ground modeling. This case study on the high-precision 3D ground model-based zonations in the area of interest verifies the usefulness in assessing spatially earthquake-induced hazards and geotechnical vulnerability and their decision-making support.

• The Journal of Engineering Geology
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• v.17 no.4
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• pp.545-554
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• 2007

Landslides is mainly induced by a heavy rainfall, earthquake ground motion, and some other factors like soil mechanics, morphological-geological factors etc. Since the starting point of the failure seemed to be originated at a construction site in the study, it is meaningful to find out the relationship between the landslide and the construction. For this study, the slope failure factor was examined carefully to see that the original natural slope had vulnerability and that the complex ground had unstability changed by construction. A field survey was conducted on the original ground surface and filled-up ground. A laboratory test was also conducted to determine the geomechanical properties of soil samples. 2D and 3D limit equilibrium analysis with changing groundwater level were conducted at the failure depth using a seismic refraction survey. The result shows that the factor of safety is similar stability under all condition, but unstable under saturated condition.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.71-80
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• 2014

This study predicted damage areas due to landslides in Gangwon Province and estimated the scale of damage to roads, buildings, and forests on the local government level. By using old research findings to predict landslides, the study established techniques to make maps for landslide vulnerability, occurrence possibility, and risk. The scale of damage to roads, buildings, and forests was estimated at the local government level by making a landslide risk map for 100mm, 200mm, and 300mm of accumulated rainfall. The scale of damage to roads, buildings, and forests was estimated to be greatest in Hongcheon-gun, Jeongseon-gun, and Hongcheon-gun, respectively, in case of 100mm~200mm accumulated rainfall, in Chuncheon City, Pyeongchang-gun, and Hongcheon-gun, respectively, in case of 200mm~300mm accumulated rainfall, and in Hongcheon-gun in case of 300mm accumulated rainfall or more. Those estimation results of scale of damage by landslides at the local government level will help to set priorities in landslide prevention and provide basic data for budget decisions.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.27-39
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• 2008

Landslides cause enormous economic losses and casualties. Korea has mountainous regions and heavy slopes in most parts of the land and has consistently built new roads and large-scale housing complexes according to its industrial and urban growth. As a result, the damage from landslides becomes greater every year. In summer, landslides frequently occur due to local torrential rains and storms. It is critical to predict the potential areas of landslides in advance and to take preventive measures to minimize consequences and to protect property and human life. The previous study on landslides mostly focused on identifying the causes of landslides in the areas where they occurred, and on analyzing landslide vulnerability around the areas without considering rainfall conditions. Thus there were not enough evaluations of the direct risk of landslides to human life. In this study, potentially risky areas for landslides were identified using the GIS data in order to evaluate direct risk on farmlands, roads, and artificial structures that were closely connected to human life. A map of landslide risk was made taking into account rainfall conditions, and a land use map was also drawn with satellite images and digital maps. Both maps were used to identify potentially risky areas for landslides.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.253-262
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• 2010

In this study, localized heavy rainfall occurred during the collapse of steep slopes adjacent to the construction site and to ensure the safety of residents to build an early warning system was performed. Forecast/Alert range was estimated based on vulnerability landslide map and past disaster history. And established a critical line in consideration of the characteristics of local rainfall and operating a snake line, the study calculated causing and non-causing points. Also, be measured in real-time analysis of rainfall data in conjunction with the system before the steep slope failure occurred forecast/Alert System is presented.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.257-257
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• 2016

현재 전 세계적으로 이상기후로 인해 자연재해가 증가하고 있으며, 우리나라 또한 집중호우, 태풍, 홍수 등의 자연재해로 인해 경제적 손실뿐만 아니라 인명피해도 증가하는 추세이다. 2014년도에만 약 2천억원의 재산피해가 발생 하였고, 5천억원 이상이 피해를 복구하는데 사용되었으며, 피해금액과 복구금액은 지속적으로 증가하고 있다. 최근 발생한 토사재해의 경우에는 인구가 밀집한 도심지에서 발생하여 매우 단기간에 치명적인 피해를 야기 시키고, 사회적 관심을 크게 일으키기도 했다. 이처럼 자연재해가 인구가 밀집되어있고, 사회적재화가 많은 도심에서 발생할 경우 그 피해규모는 더욱 커질 수 있으므로 이에 대한 적절한 대응방안이 마련되어야 한다. 본 연구에서는 대구지역에 대한 토사재해를 물리적 취약성과 사회적 취약성으로 구분하여 평가하고 이를 종합하여 평가하였다. 물리적 취약성은 Flow-R 모형을 사용하여 토사재해의 발생 가능성 및 정도를 평가하고, 발생지역의 건물 구분에 따라 그 취약성의 정도를 달리하였다. 사회적 취약성의 경우는 대구지역의 집계구 단위를 기준으로 하여, 다양한 사회적 지표에 계층분석법(Analytic Hierarchy Process, AHP)을 적용하여 지표에 대한 가중치를 산정하였다. 이후 물리적 취약성과 사회적 취약성의 값을 0에서 1사이로 정규화 시키고 정규화된 값을 다시 곱하여 0에서 1사이로 정규화 하여 취약성 정도로 나타내었다. 본 연구결과는 대구지역에 대한 토사재해의 취약성을 평가함으로써 대구 도심지에서 발생할 수 있는 토사재해 위험구역을 선정하고 방재시설을 준비하는데 있어서 기초자료로 활용될 수 있을 것으로 판단된다.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.340-351
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• 2023

Landslides are major natural geological hazards that cause enormous property damage and human casualties annually. The vulnerability of mountainous areas to landslides is further exacerbated by the impacts of climate change. Soil depth is a crucial parameter in landslide and debris flow analysis, and plays an important role in the evaluation of watershed hydrological processes that affect slope stability. An accurate method of estimating soil depth is to directly investigate the soil strata in the field. However, this requires significant amounts of time and money; thus, numerous models for predicting soil depth have been proposed. However, they still have limitations in terms of practicality and accuracy. In this study, 71 seismic survey results were collected from domestic mountainous areas to estimate soil depth on hill slopes. Soil depth was estimated on the basis of a shear wave velocity of 700 m/s, and a database was established for slope angle, elevation, and soil depth. Consequently, the statistical characteristics of soil depth were analyzed, and the correlations between slope angle and soil depth, and between elevation and soil depth were investigated. Moreover, various soil depth prediction models based on slope angle were investigated, and corrected linear and exponential soil depth prediction models were proposed.