• Explosives and Blasting
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• v.10 no.3
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• pp.8-25
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• 1992

On the Sub- way Construction It is important to Survey in advance the Geological Structure and also to make the Engineering Geological map this paper deseribs the feature of Geological structure of Seoul Area and analyses the recently occured Rock falling acciudents. NATM Tunnelling always must be done with careful observation and measurement of the geological condition.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1275-1277
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• 2003

This paper presents a geological remote sensing information extraction system, the aim of which is to provide practical models and powerful tools to extract geological information from remote sensing images for geological exploration applications. After reviewing and analyzing the existing methods for geological information extraction, we developed more than ten models to enhance and extract geological information, such as alteration information, linear features and special lithological characters. The system is developed based on Erdas Imagine using its programming language. It has been successfully used in the 'reat Investigation of Land and Natural Resources of China' program.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1442-1444
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• 2003

This paper presents a geological remote sensing information extraction system, the aim of which is to provide practical models and powerful tools to extract geological information from remote sensing images for geological exploration applications. After reviewing and analyzing the existing methods for geological information extraction, we developed more than ten models to enhance and extract geological information, such as alteration information, linear features and special lithological characters. The system is developed based on Erdas Imagine using its programming language. It has been successfully used in the ‘Great Investigation of Land and Natural Resources of China’ program.

• Geomechanics and Engineering
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• v.25 no.1
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• pp.1-16
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• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.10a
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• pp.31-33
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• 2005

• Proceedings of the Korean Geotechical Society Conference
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• 2002.11b
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• pp.103-114
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• 2002

Stability of cut-slope is considered to have a deep relationship with rock types since rock has its own engineering and geological characteristic such as shear strength, durability, weathering profile, geological structures. Therefore, analysis of geological and engineering characterisics of rock mass is essential for the evaluation of rock slope stability This paper introduces the statistical data of slope failure cases which was collected from highway slopes constructed in sedimentary rock mainly of shale in Ky ng-sang Basin. Primary failure feature in this area is planar failure along the bedding regardless of slope geometry. Even a disasterous slope failure case due to the thick clay layer between the beddings was reported. Failures and rock fall were reported to ocurred frequently after the completion of cutting due to the weathering, so long-term slope stability should be considered as a important factors in design.

• The Korean Journal of Quaternary Research
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• v.21 no.2
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• pp.69-73
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• 2007

Inorganic geochemical and mineralogical analyses from the trench sediments of the Hwayang wetland were carried out to verify the wet/dry conditions during 6000 - 5000 yr BP and abnormal event of 6300 yr BP of Korean west coast. Lithostratigraphy, mineralogy and major element concentrations of the sediments of the trench indicate that during 6000 - 5000 yr BP, a wet/dry conditions might be repeated at an interval of 200 years. Carbonate minerals precipitated with the decrease of water depth in the lake or wetland after about 6000 yr BP. On the other hand, the sediments coarser in mean grain size and larger in standard deviation were corresponded with periods of 6300 yr BP and 6230 yr BP. Especially, such a feature of grain size distribution of 6300 yr BP appears in other wetlands situated in the west coast, e.g., Hwangsan wetland and Cheollipo coastal wetland. During the period, the coarse sediments seem to have been delivered by a high energy like storming.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.11b
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• pp.236-244
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• 2005

Radioactive wastes arising from a wide range of human activities are in many different physical and chemical forms, contaminated with varying radioactivity. Their common feature is the potential hazard associated with their radioactivity and the need to manage them in such a way as to protect the human environment. The geological disposal is regarded as the most reasonable and effective way to safely disposal high-level radioactive wastes in the world. The conceptual model of geological disposal in China is based on a multi-barrier system that combines an isolating geological environment with an engineered barrier system. The buffer is one of the main engineered barriers for HLW repository. The buffer material is expected to maintain its low water permeability, self-sealing property, radio nuclides adsorption and retardation property, thermal conductivity, chemical buffering property, overpack supporting property, stress buffering property over a long period of time. Benotite is selected as the main content of buffer material that can satisfy above. GMZ deposit is selected as the candidate supplier for Chinese buffer material of High Level Radioactive waste repository. This paper presents geological features of GMZ deposit and basic property of GMZ Na bentonite. GMZ bentonite deposit is a super large scale deposits with high content of Montmorillonite (about $75\%$) and GMZ-l, which is Na-bentonite produced from GMZ deposit is selected as reference material for Chinese buffer material study.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.533-545
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• 2023

In this study, an investigation was conducted on the features, events, and processes (FEP) that could impact the long-term safety of the natural barriers constituting high-level radioactive waste geological repositories. The FEP list was developed utilizing the IFEP list 3.0 provided by the Nuclear Energy Agency (NEA) as foundational data, supplemented by geological investigations and research findings from leading countries in this field. A total of 49 FEPs related to the performance of the natural barrier were identified. For each FEP, detailed definitions, classifications, impacts on long-term safety, significance in domestic conditions, and feasibility of quantification were provided. Moreover, based on the compiled FEP list, three scenarios that could affect the long-term safety of the disposal facility were developed. Geological factors affecting the performance of the natural barrier in each scenario were selected and their relationships were visualized. The constructed FEP list and the visualization of interrelated factors in various scenarios are anticipated to provide essential information for selecting and organizing factors that must be considered in the development of mathematical models for quantitatively evaluating the long-term safety of deep geological repositories. In addition, these findings could be effectively utilized in establishing criteria related to the key performance of natural barriers for the confirmation of repository sites.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.229-237
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• 2007

To solve of complex problems for access and management data stored in the very large spatial database system that need to constructed metadata for the physical and logical elements concerned with spatial and non-spatial data sets. Also, in the underground water management system which managed with spatial and non-spatial elements, need to spatial features metadata system based on feature-based. We, in this paper, proposed metadata model for the feature-based underground water management system using underground water meta-information inputted on the DXF formatted tile-based geological maps. Additional, we modeled metadata level of feature and data set and presented standard specification of underground water metadata.