• Journal of Environmental Impact Assessment
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• v.32 no.3
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• pp.157-165
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• 2023

In Korea, a major contaminant of farmland soils in the vicinity of abandoned mines is arsenic, for which the general soil reclamation method is contaminated soil stabilization and cover the stabilized soil with clean soil at a thickness of 40 cm. In a previous pot experiment study we confirmed the feasibility of a lower thickness (20 cm) of covering soil for such reclamation in abandoned coal mines, where arsenic contamination levels are generally lower than in metal mines. In this subsequent study a field experiment including rice plant cultivation in field test plots was conducted. For over 4 months, the transfer of arsenic from the contaminated soil to the unpolished rice grains was reduced by 44% when a clean soil covering with a thickness of 20 cm was applied. The maximum decrease (56%) was shown when the stabilization process was performed before the covering. These results reveal a lower thickness of clean soil covering has a high feasibility and it can increase cost-efficiency in the reclamation of an abandoned coal mine.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.5
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• pp.98-108
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• 2009

The purpose of this study is to analyze the characteristics of limited methods, economics and breeding appropriateness of native and imported ground cover plants in the methodology of a shallow soil rooftop garden. The new shallow soil rooftop gardening method uses a total of 13cm in soil thickness, including 4.5cm of top soil on a 7.5cm rock-wool-mat stacked onto a 1cm roll-type-draining plate. The total construction cost for each method of soil level within the design price standard for SEDUM BLOCK is 89,433won/$m^2$, and for DAKU is 92,550won/$m^2$. By comparing those two methods, the construction cost of the shallow soil artificial foundation methodology is 45,000won/$m^2$; this shows the new method is 50% less expensive than the existing method of shallow soil rooftop gardening. The experiment was executed on the rooftop of the Korean National Housing Corporation to ensure validity of the shallow soil artificial foundation planting, and the sample plants which were imported and grown now in native covering. A list investigating the growing plants was made of the cover rate in each plant class, both while alive and the dry plant weight. The native ground cover plants, Sedum kamtschaticum, Sedum middendorffianum, Allium senescens, Sedum sarmentosum, Aquilegia buergariana, and Caryopteris incana increased the cover rate, live weight and dry weight in the shallow soil artificial foundation method. Among the imported cover plants, Sedum sprium and Sedum reflexum, the cover rate increased and growth conditions improved. However, some species needed weed maintenance. After examination with the less expensive shallow soil artificial foundation method and growth analysis, it was found that rooftop gardens are a low-cost option and the growth of plants is great. This result shows the new method can contribute to the proliferation of rooftop gardens in urban settings.

• Journal of Korean Society of Forest Science
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• v.90 no.3
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• pp.314-323
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• 2001

This study aimed to clarify the influencing factors of mesopore ratio on a pore geometry of surface soil in coniferous stands as an index of the water retention capacity. Twenty three factors including site conditions and soil properties were analyzed by spss/pc + for the data collected during March to October of 1993. The factors influencing the mesopore ratio(pF2.7) on the surface soil were as follows; macropore ratio(pF1.6), slope, crown-cover rates, thickness of F layer, organic matter contents, and the growing stock. And influencing factor on the ratio of mesopore in the soil surface was correlated with percentage of amount of clay, soil surface, A and B horizon soil hardness shows high negative significance. Also, multiple regression equations for mesopore ratios of surface soil and surface soil hardness, clear length, growing stock, B horizon of soil hardness, organic matter contents show high significance($R^2$; 0.80). In coniferous stands, it is effective in promoting development on the ratio of mesopore that forest practice for enhancing of the water resource retention capacity should be carried out when the crown-cover rates of stands are more than 80 percentages.

• Economic and Environmental Geology
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• v.38 no.1
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• pp.33-43
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• 2005

The purpose of this study is to make and validate landslide susceptibility map using artificial neural network and GIS in Kangneung area. For this, topography, soil, forest, geology and land cover data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, topographic type, soil texture, soil material, soil drainage, soil effective thickness, wood type, wood age, wood diameter, forest density, lithology, land cover, and lineament were used as the landslide occurrence factors. The weight of the each factor was calculated, and applied to make landslide susceptibility maps using artificial neural network. Then the maps were validated using rate curve method which can predict qualitatively the landslide occurrence. The landslide susceptibility map can be used to reduce associated hazards, and to plan land use and construction as basic data.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.14 no.2
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• pp.189-200
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• 2016

The Republic of Tajikistan has ten former uranium mining sites. The total volume of all tailings is approximately 55 million tonnes, and the covered area is more than 200 hectares. The safe management of legacy uranium mining and tailing sites has become an issue of concern. Depending on the performance requirements and site-specific conditions (location in an arid, semiarid or humid region), a cover system for uranium tailings sites could be constructed using several material layers using both natural and man-made materials. The purpose of this study is to find a feasible cost-effective cover system design for the Degmay uranium tailings site which could provide a long period (100 years) of protection. The HELP computer code was used in the evaluation of potential Degmay cover system designs. As a result of this study, a cover system with 70 cm thick percolation layer, 30 cm thick drainage layer, geomembrane liner and 60 cm thick barrier soil layer is recommended because it minimizes cover thickness and would be the most cost-effective design.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.256-272
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• 2002

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and to apply the newly developed techniques to the study area of Boun in Korea. Landslide locations were identified in the study area from interpretation of aerial photographs, field survey data, and a spatial database of the topography, soil type, timber cover, geology and land use. The landslide-related factors (slope, aspect, curvature, topographic type, soil texture, soil material, soil drainage, soil effective thickness, timber type, timber age, and timber diameter, timber density, geology and land use) were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network methods. For this, the weights of each factor were determinated in 3 cases by the backpropagation method, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated and the susceptibility maps were made with a GIS program. The results of the landslide susceptibility maps were verified and compared using landslide location data. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to maintain precision and accuracy.

• Geomechanics and Engineering
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• v.11 no.4
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• pp.471-492
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• 2016

Underground tunnelling is one of the sustainable construction methods which can facilitate the increasing passenger transportation in the urban areas and benefit the community in the long term. Tunnelling in various ground conditions requires careful consideration of the stability factor. This paper investigates three dimensional stability of a shallow circular tunnel in a layered soil. Upper bound theorem of limit analysis was utilised to solve the tunnel face stability problem. A three dimensional kinematic admissible failure mechanism was improved to model a layered soil and limiting assumptions of the previous studies were resolved. The study includes calculation of the minimum support pressure acting on the face of the excavation in closed-face excavations. The effects of the characteristics of the layers on the minimum support pressure were examined. It was found that the ratio of the thickness of cover layers particularly when a weak layer is overlying a stronger layer, has the most significant influence on the minimum tunnel support pressure. Comparisons have been made with the results of the numerical modelling using FLAC3D software. Results of the current study were in a remarkable agreement with those of numerical modelling.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.298-301
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• 2004

The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.64-64
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• 2003

The aim of this study is to apply and verify of logistic regression at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database.13${\times}$1ure, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the logistic regression coefficient were overlaid for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.