• Journal of the Korean earth science society
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• v.35 no.2
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• pp.131-146
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• 2014

Multi-beam echosounder data and grain size analysis data of surface sediment were acquired and analyzed in order to investigate the shelf-to-slope morphology, geological character, and their geological controlling factors in the southwestern margin of the Ulleung Basin. According to the morphological character, the continental shelf can be divided into two parts: (1) shallow (~100 m) and steep ($0.5^{\circ}$) inner shelf, (2) deep (100-300 m) and gentle ($0.2^{\circ}$) outer shelf. The continental slope is featured with eight distinct topographic depressions of various spatial dimension (~121 $km^2$ in area) and head wall gradient (${\sim}24.3^{\circ}$). They are developed adjacent to each other and presumably formed by submarine landslides which have recurred under the strong influences of earthquakes and eustatic sea-level change. The inner continental shelf and the continental slope are dominated by fine-grained sediment, whereas the outer continental shelf is dominated by coarse-grained sediment. The surface sediment distribution seems dominantly influenced by eustatic sea-level change. The outer continental shelf is mostly covered by coarse relict sediment deposited during lowstand sea-level, while the inner shelf is covered with recent sediment during highstand sea-level. The surface of the continental slope is covered with fine-grained sediments which were supplied by hemipelagic advection process.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.610-621
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• 2021

The soil creep, primarily caused by earthquakes and torrential rainfall events, has widely occurred across the country. The Korea Forest Service attempted to quantify the soil creep susceptible areas using a discriminant value table to prevent or mitigate casualties and/or property damages in advance. With the advent of advanced computer technologies, machine learning-based classification models have been employed for managing mountainous disasters, such as landslides and debris flows. This study aims to quantify the soil creep susceptibility using several classifiers, namely the k-Nearest Neighbor (k-NN), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) models. To develop the classification models, we downscaled 292 data from 4,618 field survey data. About 70% of the selected data were used for training, with the remaining 30% used for model testing. The developed models have the classification accuracy of 0.727 for k-NN, 0.750 for NB, 0.807 for RF, and 0.750 for SVM against test datasets representing 30% of the total data. Furthermore, we estimated Cohen's Kappa index as 0.534, 0.580, 0.673, and 0.585, with AUC values of 0.872, 0.912, 0.943, and 0.834, respectively. The machine learning-based classifications for soil creep susceptibility were RF, NB, SVM, and k-NN in that order. Our findings indicate that the machine learning classifiers can provide valuable information in establishing and implementing natural disaster management plans in mountainous areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of Korean Society of Forest Science
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• v.110 no.1
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• pp.64-71
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• 2021

Recently, climate change has gradually accelerated the occurrence of landslides. Among the various effects caused by landslides,debris flow is recognized as particularly threatening because of its high speed and propagating distance. In this study, the impacts of various factors were analyzed using quantification theory(I) for the prediction of debris flow hazard soil volume in Seoraksan National Park, Korea. According to the range using the stepwise regression analysis, the order of impact factors was as follows: vertical slope (0.9676), cross slope (0.6876), altitude (0.2356), slope gradient (0.1590), and aspect (0.1364). The extent of the normalized score using the five-factor categories was 0 to 2.1864, with the median score being 1.0932. The prediction criteria for debris flow occurrence based on the normalized score were divided into four grades: class I, >1.6399; class II, 1.0932-1.6398; class III, 0.5466-1.0931; and class IV, <0.5465. Predictions of debris flow occurrence appeared to be relatively accurate (86.3%) for classes I and II. Therefore, the prediction criteria for debris flow will be useful for judging the dangerousness of slopes.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.29-36
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• 2021

Recently, due to climate change, the slope is increasing, and the risk of steep slope disasters such as the occurrence of slope collapse in the east coast and Busan region in 2019 and the Gokseong landslide in 2020 is increasing. Particularly, most national parks are made up of mountainous areas, and the risk of disasters on steep slopes is increasing. As the ground of the national park is aging and the weathering and jointing of the bedrock are accelerating due to climate change, the slope collapse and rockfall are increasing, and the annual number of visitors is increasing, it is necessary to manage steep slopes adjacent to multi-use facilities with many users. In this study, dangerous steep slopes that affect multi-use facilities in national parks were analyzed using GIS and verified through field surveys. As a process for extracting steep slopes adjacent to multi-use facilities in national parks, the slope was made in DEM and slopes of 34 degrees or higher were extracted. The difference between the maximum and minimum heights of the extracted slopes was used to confirm that the slopes met the standard for steep slopes, and the analysis of the slope direction was used to confirm whether it had an effect on the multi-use facilities. After that, precision aerial images and field photos were analyzed to finally identify risks at 4 sites, and field surveys were conducted. As a result of the field survey, all 4 sites were found to be steep slopes, 3 were graded D and 1 was graded C, so it was confirmed that management was required as a risk of collapse. All steep slopes extracted through GIS were found to be dangerous, so it is judged that the extraction of steep slopes through GIS would be appropriate.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.31-38
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• 2022

Recently, irregular torrential rainfall have frequently occurred due to abnormal climate, and landslide damage is increasing. In Korea, more than 70% of the total land is mountainous areas, appropriate measures are needed to prevent landslides by heavy rainfall. When improved soil is applied to the surface of the slope, it is possible to suppress an increase in groundwater level due to rainfall penetration and secure stability of the slope. In this study, the appropriate depth of improved soil that can confirm the increase in groundwater level and secure stability by applying improved soil to the weathered soil slope was studied. A total of three cases were analyzed for the slope of the cross-section: standard slope for weathered soil (1:1.5, 1:1.8, and 1:2.0). For rainfall conditions, referring to the regional frequency probability rainfall provided by the Water resource Management Information System, the increase in groundwater level by stage was confirmed by assuming a 500-year frequency precipitation maximum duration of 48 hours. As a result of the study, in the case of natural slopes, the slope was completely saturated before 48 hours the rainfall duration, and there was a possibility of collapse. the improvement depth in the slope of 1:1.5 was appropriate for more than 1m from the surface regardless of the rainfall duration, and in the the slope of 1:1.8 was appropriate of 1m for more than 36 hours. in the slope of 1:2.0, it was appropriate for that safety when improved soil of 0.5m for rainfall duration 48 hours or more.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.69-83
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• 2023

Forest fires increase the risk of subsequent soil erosion and mass movement in burned areas, even under rainfall conditions below landslide alert thresholds, by destroying plants and vegetation and causing changes to soil properties. These effects of forest fires can alter runoff in burned areas by altering soil composition, component minerals, soil water repellency, soil mass stability, and soil fabric. Heat from forest fires not only burns shallow organic matter and plants but also spreads below the surface, affecting soil constituents including minerals. This study analyzed X-ray diffraction and physical properties of topsoil and subsoil obtained from both burned and non-burned areas to identify the composition and distribution of clay minerals in the soil. Small amounts of mullite, analcite, and hematite were identified in burned soils. Vermiculite and mixed-layer illite/vermiculite (I/V) were found in topsoil samples from burned areas but not in those from non-burned areas. These findings show changes in soil mineral composition caused by forest fires. Expansive clay minerals increase the volume of soil during rainfall, degrading the structural stability of slopes. Clay minerals generated in soil in burned areas are therefore likely to affect the long-term stability of slopes in mountainous areas.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• The Journal of Engineering Geology
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• v.17 no.1 s.50
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• pp.15-25
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• 2007

In general, the life and asset casualties that occur due to landslide or slope failure in urban areas are larger than that in rural areas. In order to reduce the casualties, a slope management program is necessary to categorize slopes based on properties and to manage them systematically. The slope management system is the establishment of the data base for the geological and geotechnical factor according to slope stability, and the utilization of the data base to manage slopes. The suitable system must develop to slopes in urban area through the survey, analysis and evaluation process. Based on the above necessity, the slope management program which is applicable to slope management in an urban area has been developed at Hwangryung Mt. in Busan as a target area. The developed slope management program has various functions such as slope ID number of each slope or sub-region of a mountain, making a slope data sheet, analysis and grouping of slope stability, and establishment of a data base. The slope management program is constructed by use of GIS, and the survey, test and analysis data according to all slopes can be input and edited into the program. The program can also be utilized practically by end users due to the convenient input, edition printing, management and operation of slope data. Therefore, the slope management system has been established on the application of the developed program in Busan which is located in slope area. As the system is widely applied to other cities, the slope in urban area can be managed systematically and the slope hazards can be minimized.