• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.288-295
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• 2003

The relationship between the reflection number obtained from seismic reflective survey and the rock strength value obtained from TBM excavation is examined, and the procedure of the conversion from the reflection number to the rock strength value is proposed. Subsequently, geostatistical method is employed to evaluate the rock properties ahead of the tunnel face and around the tunnel with good precision, using both the seismic reflective survey data and the TBM driving data for the purpose of the tunnel driving and enlargement. The applicability of this evaluation method is examined at the actual tunnel site.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.05a
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• pp.101-118
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• 2009

In order to invest in overseas mineral projects, it is necessary to have a ability of technical and financial evaluation. Reserve estimation is the most important for mineral appraisal. Geostatistical evaluation of tonnage and grade promises more accurate reserve estimation than traditional methods such as polygon, inverse distance method and so on even if it has some uncertainty. Selection of a mining method and a mineral processing is also important because capex and opcosts of a mineral project is due to the selection. Mineral project is usually evaluated financially using NPV and IRR which are calculated through DCF(Discount Cash Flow). Uncertainty of a mineral project is analyzed statistically using sensitivity analysis and montecarlo simulation.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.1
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• pp.3-13
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• 2007

In this study, spatial characteristics of rainfall in Imha basin were investigated by cross-correlation analysis among rainfall gaging stations and rainfall-runoff analysis used in HEC-HMS model for analysis of influence on observed rainfall. The Kriging technique was applied to rain(all analysis in Imha basin to reflect spatial characteristics of regional rainfall. Their results are compared to rainfall-runoff data with spatially distributed rainfall data as well as the classical thiessen method. The results by kriging technique approached by geostatistical method could reflect spatial characteristics of regional rainfall properly in Imha basin.

• Nuclear Engineering and Technology
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• v.30 no.6
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• pp.485-495
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• 1998

Migration characteristics of tracers in a rock fracture in a case of line-source and line-collection was studied. The fracture plane was discretized into a square mesh to which variable apertures were assigned. The spatially varying apertures of a fracture were generated using a geostatistical method, based on a given aperture probability density distribution and a specified spatial correlation length. The flow potential and pressure at each node were computed. Calculations showed that fluid flow occurs predominantly through a few preferred paths. Hence, the large range of apertures in the fracture gives rise to flow channeling. The solute transport was calculated using a particle tracking method. The migration plumes of tracer between injection line and withdrawal line are displayed in contour plots. The elution curves are shown to be controlled by the aperture density distribution and to be insensitive to statistical realization and spatial correlation length.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.138-147
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• 2010

As inaccurate traffic volume prediction may result in inadequate transportation planning and design, traffic volume prediction based on traffic volume data is very important in spatial decision making processes such as transportation planning and operation. In order to improve the accuracy of traffic volume prediction, recent studies are using the geostatistical approach called kriging and according to their reports, the method shows high predictability compared to conventional methods. Thus, this study estimated traffic volume data for St. Louis in the State of Missouri, USA using the kriging method, and tested its accuracy by comparing the estimates with actual measurements. In addition, we suggested a new method for enhancing the accuracy of prediction by the kriging method. In the new method, we estimated traffic volume data: first, by applying anisotropy, which is a characteristic of traffic volume data appearing in determining variogram factors; and second, by performing co-kriging analysis using interstate highway, which is in a high spatial correlation with traffic volume data, as a secondary variable. According to the results of the analysis, the analysis applying anisotropy showed higher accuracy than the kriging method, and co-kriging performed on the application of anisotropy produced the most accurate estimates.

• Economic and Environmental Geology
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• v.30 no.5
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• pp.493-498
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• 1997

The purpose of this study is to develop geostatistical model for evaluating the abundance of deep-sea manganese nodule. The abundance data used in this study were obtained from the KODOS (Korea Deep Ocean Study) area. The variation of nodule abundance was very high within short distance, while sampling methods was very limited. As the distribution of nodule abundance showed non-gaussian, indicator simulation method was used instead of conditional simulation method and/or ordinary kriging. The abundance data were encoded into a series of indicators with 6 cutoff values. They were used to estimate the conditional probability distribution function (cpdf) of the nodule abundance at any unsampled location. The standardized indicator variogram models were obtained according to variogram analysis. This SIS method had the advantage over other traditional techniques such as the turning bands method and ordinary kriging. The estimating values by indicator conditional simulation near high abundance area were more detailed than by ordinary kriging and indicator kriging. They also showed better spatial characteristics of distribution of nodule abundance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.95-104
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• 2018

This study has the purpose of suggesting the method to analyze the spatiotemporal change of satisfaction concerning the officially assessed land price using geostatistical analysis. Analyzing the spatial distribution characteristic of officially assessed land price using present GIS (Geographic Information System) or is staying at qualitatively suggesting the improvement method of the officially assessed land price system. Grouping the appeal strength based on the official price and opinion price of officially assessed land price, GIS DB (Database) was constructed and the time seriate satisfaction were analyzed and compared through spatial density analysis and spatial autocorrelation analysis. As a result, it was found that the difference between the official price and the applicant's price differed depending on individual land, but most of the respondents requested the increase or the reduction of the average land price, which resulted in a large number of request. Analyzing the satisfaction of the officially assessed land price by using GIS, it was known that satisfaction of officially assessed land price could be analyzed by using the difference of the opinion price and not only the officially assessed land price. Spatiotemporal change of officially assessed land price satisfaction was known to be possible through spatiotemporal pattern analysis method such as spatiotemporal auto-corelation analysis and hotspot analysis etc using GIS. In short, regionally positive or negative significant relationship was investigated through spatiotemporal analysis using annual data.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.340-343
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• 2003

This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.57-76
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• 2007

Kriging is a nonparametric regression method used in geostatistics for estimating curves and surfaces for spatial data. It may come as a surprise that the Kriging estimator, normally derived as the best linear unbiased estimator, is also the solution of a particular variational problem. Thus, Kriging estimators can also be interpreted as generalized smoothing splines where the roughness penalty is determined by the covariance function of a spatial process. We build off the early work by Silverman (1982, 1984) and the analysis by Cox (1983, 1984), Messer (1991), Messer and Goldstein (1993) and others and develop an equivalent kernel interpretation of geostatistical estimators. Given this connection we show how a given covariance function influences the bias and variance of the Kriging estimate as well as the mean squared prediction error. Some specific asymptotic results are given in one dimension for Matern covariances that have as their limit cubic smoothing splines.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.262-265
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• 2000

In order to estimate spatial physicochemical properties of the spring waters in the study area, spring waters at 57 sites were investigated for measuring ten items (temperature, pH, Eh, EC, TDS, DO, salinity, alkalinity, discharge rate, and surface elevation), To compare each component with one another, regression analysis was carried out. Kriging was used to estimate the spatial characteristics and continuity of data in the study area. To solve kriging equation, the semivariogram was calculated using geostatistical software GS$^{+}$(version 3.1). As a result of semivariogram analysis, the data of nine components but surface elevation could be assumed as stationary random function, and ordinary kriging method was used for making contour maps.s.