• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.435-450
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• 2005

The purpose of the study is to analyze the hydrogeochemical characteristics by multivariate statistical method, to interpret the hydrogeochemical processes for the new variables calculated from principal components analysis (PCA), and to infer the groundwater flow and circulation mechanism by applying the geostatistical methods for each element and principal component. Chloride and nitrate are the most influencing components for groundwater quality, and the contents of $NO_3$ increased by the input of agricultural activities show the largest variation. The results of PCA, a multivariate statistical method, show that the first three principal components explain $73.9\%$ of the total variance. PC1 indicates the increase of dissolved ions, PC2 is related with the dissolution of carbonate minerals and nitrate contamination, and PC3 shows the effect of cation exchange process and silicate mineral dissolution. From the results of experimental semivariogram, the components of groundwater are divided into two groups: one group includes electrical conductivity (EC), Cl, Na, and $NO_3$, and the other includes $HCO_3,\;SiO_2,$ Ca, and Sr. The results for spatial distribution of groundwater components showed that EC, Cl, and Na increased with approaching the coastal line and nitrate has close relationship with the presence of agricultural land. These components are also correlated with the topographic features reflecting the groundwater recharge effect. The kriging analysis by using principal components shows that PC 1 has the different spatial distribution of Cl, Na, and EC, possibly due to the influence of pH, Ca, Sr, and $HCO_3$ for PC1. It was considered that the linear anomaly zone of PC2 in western area was caused by the dissolution of carbonate mineral. Consequently, the application of multivariate and geostatistical methods for groundwater in the study area is very useful for determining the quantitative analysis of water quality data and the characteristics of spatial distribution.

• Economic and Environmental Geology
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• v.28 no.3
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• pp.199-211
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• 1995

The deep sea camera system could render it possible to obtain the detailed information of the nodule distribution, but difficult to estimate nodule abundance quantitatively. In order to estimate nodule abundance quantitatively from deep seabed photographs, the nodule abundance equation was derived from the box core data obtained in KODOS area(long.: $154^{\circ}{\sim}151^{\circ}W$, lat.: $9^{\circ}{\sim}12^{\circ}N$) during two survey cruises carried out in 1989 and 1990. The regression equation derived by considering extent of burial of nodule to Handa's equation compensates for the abundance error attributable to partial burial of some nodules by sediments. An average long axis and average extent of burial of nodules in photographed area are determined according to the surface textures of nodules, and nodule coverage is calculated by the image analysis method. Average nodule abundance estimated from seabed photographs by using the equation is approximately 92% of the actual average abundance in KODOS area. The measured sampling points by box core or free fall grab are in general very sparse and hence nodule abundance distribution should be interpolated and extrapolated from measured data to uncharacterized areas. The another goal of this study is to depict continuous distribution of nodule abundance in KODOS area by using PC-version of geostatistical model in which several stages are systematically proceeded. Geostatistics was used to analyse spatial structure and distribution of regionalized variable(nodule abundance) within sets of real data. In order to investigate the spatial structure of nodule abundance in KODOS area, experimental variograms were calculated and fitted to a spherical models in isotropy and anisotropy, respectively. The spherical structure models were used to map out distribution of the nodule abundance for isotropic and anisotropic models by using the kriging method. The result from anisotropic model is much more reliable than one of isotropic model. Distribution map of nodule abundance produced by PC-version of geostatistical model indicates that approximately 40% of KODOS area is considered to be promising area(nodule abundance > $5kg/m^2$) for mining in case of anisotropy.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.525-536
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• 2011

In any applications using various types of spatial data, it is very important to account for the scale differences among available data sets and to change the scale to the target one as well. In this paper, we propose to use a geostatistical downscaling approach based on vaiorgram deconvloution and block simulation to generate fine-scale categorical thematic maps from coarse-scale fraction data. First, an iterative variogram deconvolution method is applied to estimate a point-support variogram model from a block-support variogram model. Then, both a direct sequential simulation based on area-to-point kriging and the estimated point-support variogram are applied to produce alternative fine-scale fraction realizations. Finally, a maximum a posteriori decision rule is applied to generate the fine-scale categorical thematic maps. These analytical steps are illustrated through a case study of land-cover mapping only using the block fraction data of thematic classes without point data. Alternative fine-scale fraction maps by the downscaling method presented in this study reproduce the coarse-scale block fraction values. The final fine-scale land-cover realizations can reflect overall spatial patterns of the reference land-cover map, thus providing reasonable inputs for the impact assessment in change of support problems.

• Journal of the Korean GEO-environmental Society
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• v.15 no.3
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• pp.65-74
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• 2014

Borehole investigation which is mainly used to figure out geotechnical characterizations at construction work has the benefit that it provides a clear and convincing geotechnical information. But it has limitations to get the overall information of the construction site because it is performed at point location. In contrast, geophysical measurements like seismic survey has the advantage that the geological stratum information of a large area can be characterized in a continuous cross-section but the result from geophysics survey has wide range of values and is not suitable to determine the geotechnical design values directly. Therefore it is essential to combine borehole data and geophysics data complementally. Accordingly, in this study, a three-dimensional spatial interpolation of the cross-sectional distribution of seismic refraction was performed using digitizing and geostatistical method (krigring). In the process, digital map were used to increase the trustworthiness of method. Using this map, errors of ground height which are broken out in measurement from boring investigation and geophysical measurements can be revised. After that, average seismic velocity are derived by comparing borehole data with geophysical speed distribution data of each soil layer. During this process, outlier analysis is adapted. On the basis of the average seismic velocity, integrated analysis techniques to determine the three-dimensional geological stratum information is established. Finally, this analysis system is applied to dam construction field.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.59-70
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• 2022

There is a growing interest in evaluating earthquake damage and determining disaster prevention measures due to the magnitude 5.8 earthquake in Pohang, Korea. Since the liquefaction phenomena occurred extensively in the residential area as a result of the earthquake, there was a demand for research on liquefaction phenomenon evaluation and liquefaction disaster prediction. Liquefaction is defined as a phenomenon where the strength of the ground is completely lost due to a sudden increase in excess pore water pressure caused due to large dynamic stress, such as an earthquake, acting on loose sand particles in a short period of time. The liquefaction potential index, which can identify the occurrence of liquefaction and predict the risk of liquefaction in a targeted area, can be used to create a liquefaction hazard map. However, since liquefaction assessment using existing field testing is predicated on a single borehole liquefaction assessment, there has been a representative issue for the whole targeted area. Spatial interpolation and geographic information systems can help to solve this issue to some extent. Therefore, in order to solve the representative problem of geotechnical information, this research uses the kriging method, one of the geostatistical spatial interpolation techniques, and constructs a geotechnical information database for liquefaction and spatial interpolation. Additionally, the liquefaction hazard map was created for each return period using the constructed geotechnical information database. Cross validation was used to confirm the accuracy of this liquefaction hazard map.

• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.3
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• pp.171-180
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• 2016

Earthquake event keeps increasing every year, and the recent cases of earthquake hazards invoke the necessity of seismic study in Korea, as geotechnical earthquake hazards, such as strong ground motion, liquefaction and landslides, are a significant threat to structures in industrial hub areas including coastal facilities. In this study, systemized framework of integrated assessment of earthquake-induced geotechnical hazard was established using advanced geospatial database. And a visible simulation of the framework was specifically conducted at two coastal facility areas in Incheon. First, the geospatial-grid information in the 3D domain were constructed with geostatistical interpolation method composed of multiple geospatial coverage mapping and 3D integration of geo-layer construction considering spatial outliers and geotechnical uncertainty. Second, the behavior of site-specific seismic responses were assessed by incorporating the depth to bedrock, mean shear wave velocity of the upper 30 m, and characteristic site period based on the geospatial-grid. Third, the normalized correlations between rock-outcrop accelerations and the maximum accelerations of each grid were determined considering the site-specific seismic response characteristics. Fourth, the potential damage due to liquefaction was estimated by combining the geospatial-grid and accelerations correlation grid based on the simplified liquefaction potential index evaluation method.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.319-326
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• 2003

In site investigation for tunnel designs, nowadays, geophysical exploration such as seismic exploration and electric resistivity exploration as well as drilling logging is frequently carried out. A method which can systematically make the utmost use of all available data obtained from investigation, therefore, is strongly required for the optimal evaluation of ground conditions in terms of rock mass class, etc. Many researchers have proposed using qualitative data to cope with the lack of quantitative data. In this study, an evaluation technique of rock mass classes in undrilled region was proposed based upon multiple indicator kriging method which is a geostatistical technique. It was shown that two types of data with different degree of uncertainty, for example, drilling logging data and geophysical exploration data, could be simultaneously utilized in evaluating rock mass classes for a real tunnel design.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.475-487
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• 2024

Many uncertainties affect the stability assessment of rock structures. Some of these factors significantly influence technology decisions. Some of these factors belong to the geological domain, and spatial uncertainty measurements are useful for structural stability analysis. This paper presents an integrated approach to study the stability of rock structures, including spatial factors. This study models two main components: discrete structures (fault zones) and well known geotechnical parameters (rock quality indicators). The geostatistical modeling criterion are used to quantify geographic uncertainty by producing simulated maps and RQD values for multiple equally likely error regions. Slope stability theorem would be demonstrated by modeling local failure zones and RQDs. The approach proided is validated and finally, the slope stability analysis method and fuzzy Laypunov criterion are applied to mining projects with limited measurement data. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and fuzzy theory.

• Economic and Environmental Geology
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• v.35 no.2
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• pp.137-147
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• 2002

Natural geological and environmental processes reflect to element abundances in geological materials on the surface. This study aims to elucidate a possibility of geostatistical application to differentiate geochemical anomalies affected by anthropogenic and geogenic factors. A regional geochemical map was produced using 'inverse distance weight interpolation' method for analytical results of stream sediments «150 11m) which were collected from 2,290 first- to second-order streams over the whole Gyeonggi Province. The Jurassic granitic batholith in the southeastern province was selected as a target for the geostatistical examination. Factor analysis was conducted using 22 elements for stream sediments from 445 drainage basins over the granitic body. Co, Cr, Sc, MgO, Fe$_{2}$O$_{3}$, V, and Ni were grouped with high correlation coefficients and the depletion of the components may reflect the whole-rock chemistry of the granite. Regression analysis was done using Co, Cr, and Sc as dependent variables and other six components as independent variables, and the results were drawn as maps. The maps acquired generally show quite similar distribution patterns with those of concentrations of each variable. The similarity in the spatial patterns between the two maps indicates that the application of regression statistics can be valid for the interpretation of regional geochemical data. However, some components show local discrepancies which may be influenced by secondary factors regardless of the basement lithology. The regression analysis may be effective in extracting local geochemical anomalies which may reflect rather anthropogenic pollutions than geogenic influences.

• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.879-890
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• 2011

The GOSAT (Greenhouse gases Observing SATellite) data provide new opportunities the most regionally complete and up-to-date assessment of $CO_2$. However, in practice, GOSAT records often suffer from missing data values mainly due to unfavorable meteorological condition in specific time periods of data acquisition. The aim of this research was to identify optimal spatial interpolation techniques to ensure the continuity of $CO_2$ from samples taken in the North East Asia. The accuracy among ordinary kriging (OK), universal kriging (UK) and simple kriging (SK) was compared based on the combined consideration of $R^2$ values, Root Mean Square Error (RMSE), Mean Error (ME) for variogram models. Cross validation for 1312 random sampling points indicate that the (UK) kriging is the best geostatistical method for spatial predictions of $CO_2$ in the East Asia region. The results from this study can be useful for selecting optimal kriging algorithm to produce $CO_2$ map of various landscapes. Also, data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the GOSAT sample data.