• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.39-47
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• 2003

The purpose of this paper is to present the method of acquiring 3D GIS data using the statistical estimating methods of Well Log for balancing Seismic data. We use the reflection coefficients of seismic data to get the parameters for the reservoir characterization and we balance the reflection coefficients of seismic data using well log to increase the confidence of the estimated result. Well logs are required to balance the reflection coefficients at the point where seismic data are acquired. In this research, we discuss the geostatistical estimation methods and we applied these methods to real data. Kriging gives high weights to the close well logs, which means estimated results are mainly affected by close well log. High value of cross variograms gave big difference on cokriging result comparing to kriging results and low value of cross variogram gave little differences.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.415-427
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• 2001

공간통계학에서는 다변량 공간자료에 대한 예측방법으로서 코크리깅 기법을 이용한다. 본 논문에서는 코크리깅을 위한 첫 번째 단계인 교차베리오그램의 추정에 대한 감도분석 대신에 일반통계학적 측면에서 주성분점수를 이용한 감도분석방법을 제안한다. 변수가 2개인 경우, 교차베리오그램에 대한 감조분석의 결과와 제안된 주성분점수를 이용한 감도분석의 결과를 비교해 본다. 모의실험을 통하여 제안한 방법의 타당을 검증하고, 실제 자료를 이용한 사례분석의 결과로써 재확인해 본다.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.83-92
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• 2020

The purpose of this work was to apply geographical information system (GIS) for geostatistical analyzing by selecting a semi-variogram model to quantify the spatial correlation of the population distribution with residential neighborhoods in the both sides of Mosul city. Two hundred and sixty-eight sample sites in 240 ㎢ are adopted. After determining the population distribution with respect to neighborhoods, data were inserted to ArcGIS10.3 software. Afterward, the datasets was subjected to the semi-variogram model using ordinary kriging interpolation. The results obtained from interpolation method showed that among the various models, Spherical model gives best fit of the data by cross-validation. The kriging prediction map obtained by this study, shows a particular spatial dependence of the population distribution with the neighborhoods. The results obtained from interpolation method also indicates an unbalanced population distribution, as there is no balance between the size of the population neighborhoods and their share of the size of the population, where the results showed that the right side is more densely populated because of the small area of residential homes which occupied by more than one family, as well as the right side is concentrated in economic and social activities.

• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2003.10a
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• pp.71-71
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• 2003

• Journal of the Korean Geotechnical Society
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• v.26 no.1
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• pp.5-19
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• 2010

Geo-layer information is important to determine pile length and estimate residual settlement in the construction site. An overall spatial distribution of geo-layers in the entire construction site can be predicted using drill-log information. In this study, the geo-layer distribution at Song-do area was estimated by kriging and inverse distance weighting methods, and a cross validation was adopted to verify the reliability of estimation results. The analysis results indicate that the best fitted theoretical variogram model to the experimental variogram does not always provide the most reliable estimation in the kriging method. The proper $\alpha$ value of inverse distance weighting method must be determined by types of geo-layer, because the $\alpha$ value is affected by types of geo-layer. Results of the kriging method show more reliable results than those of inverse distance weighting method, and the structure of geo-layer distribution could be evaluated by variogram in the kriging method.

• Economic and Environmental Geology
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• v.28 no.3
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• pp.271-277
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• 1995

The geological information analysis based on spatial statistical techniques have been studied in relation to mineral exploration. The applicability of outlier detection using moving-window statistics and directional cross-variography analysis have been verified by using geochemical data sets surveyed in the Taebaek area for mineral exploration. The directional variogram analysis has been basically known as a geostatistical method for spatial continuity measures. In this study, the application of this proposed method was extended to measure spatial correlation or similarity problems between two geochemical elements. For the appraisal of the usefulness of this scheme, five kinds of variogram functions were computed for original data and revised data, obtained by removing outliers detected by moving-window statistics and the results were compared. It is concluded that these advanced spatial statistical methods at the interpretation stage of spatial similarity provide us with valuable quantitative results as decision-supporting information for regional mineral exploration task.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.1093-1107
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• 2008

In this study, we considered linear regression model with various spatial dependency structures in order to make more reliable prediction of precipitation in South Korea. The prediction approaches are based on semi-variogram models fitted by least-squares estimation method and restricted maximum likelihood estimation method. We validated some candidate models from the two different estimation methods in terms of cross-validation and comparison between predicted values and observed values measured at different locations.

• Journal of the Korean Geotechnical Society
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• v.38 no.10
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• pp.17-29
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• 2022

Recently, the interest in integrated underground geospatial information mapping (IUGIM) to ensure the safety of underground spaces and facilities has been increasing. Because IUGIM is used in the fields of underground space development and underground safety management, the up-to-dateness and accuracy of information are critical. In this study, IUGIM and field data were classified, and the accuracy of IUGIM was improved by spatial interpolation. A spatial interpolation technique was used to process borehole data in IUGIM, and a quantitative evaluation was performed with mean absolute error and root mean square error through the cross-validation of seven interpolation results according to the technique and model. From the cross-validation results, accuracy decreased in the order of nonuniform rational B-spline, Kriging, and inverse distance weighting. In the case of Kriging, the accuracy difference according to the variogram model was insignificant, and Kriging using the spherical variogram exhibited the best accuracy.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.352-361
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• 2003

We have evaluated the extent of saltwater intrusion from electrical resistivity distribution in a coastal aquifer system in the southeastern part of Busan, Korea. This aquifer system is divided into four layers according to the hydrogeologic characteristics and the horizontal extent of intruded saltwater is determined at each layer through the geostatistical interpretation of electrical resistivity data. In order to define the statistical structure of electrical resistivity data, variogram analysis is carried out to obtain best generalized covariance models. IRF-k (intrinsic random function of order k) kriging is performed with covariance models to produce the plane of spatial mean resistivities. The kriged estimates are evaluated by cross validation to show a good agreement with the true values and the statistics of cross validation represented low errors for the estimates. In the resistivity contour maps more than 5 m below the surface, we can see a dominant direction of saltwater intrusion beginning from the east side. The area of saltwater intrusion increases with depth. The northeast side has low resistivities less than 5 ohm-m due to the presence of saline water in the depth range of 20 m through 70 m. These results show that the application of geostatistical technique to electrical resistivity data is useful for assessing saltwater intrusion in a coastal aquifer system.

• Spatial Information Research
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• v.22 no.1
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• pp.9-17
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• 2014

This study was intended to reliably predict the traffic green house gas emission in Daegu with the use of spatial statistical technique and calculate the traffic green house gas emission of each administrative district on the basis of the accurately predicted emission. First, with the use of the traffic actually surveyed at a traffic observation point, and traffic green house gas emission was calculated. Secondly, on the basis of the calculation, and with the use of Universal Kriging technique, this researcher set a suitable variogram modeling to accurately and reliably predict the green house gas emission at non-observation point suitable through spatial correlation, and then performed cross validation to prove the validity of the proper variogram modeling and Kriging technique. Thirdly, with the use of the validated kriging technique, traffic green gas emission was visualized, and its distribution features were analyzed to predict and calculate the traffic green house gas emission of each administrative district. As a result, regarding the traffic green house gas emission of each administration, it was found that Bukgu had the highest green house gas emission of $291,878,020kgCO_2eq/yr$.