• 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 $291,878,020kgCO_2eq/yr$.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.146-156
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• 2010

The objective of this study was to improve the accuracy of calculation and estimation of solar radiation and duration of sunshine, which are the most important variables of photovoltaic power generation in deciding the location of photovoltaic facilities efficiently. With increasing interest in new and renewable energies, research on solar energy is also being conducted actively, but there have not been many studies on the location of photovoltaic facilities. Thus, this study calculated solar duration and solar radiation based on geographical factors, which have the most significant effect on solar energy in GIS environment, and corrected the results of analysis using diffuse radiation. Moreover, we performed ordinary kriging, a spatial statistical analysis method, for estimating values for parts deviating from the spatial resolution of input data, and used variogram, which can determine the spatial interrelation and continuity of data, in order to estimate accurate values. In the course, we compared the values of variogram factors and estimates from applicable variogram models, and selected the model with the lowest error rate. This method is considered helpful to accurate decision making on the location of photovoltaic facilities.

• 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.

• Journal of the Korean Society of Groundwater Environment
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• v.1 no.2
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• pp.113-120
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• 1994

One of the delicate problems in aquifer management is the identification of the spatial distribution of tile hydrological parameters. The observed data are insufficient to identify the distribution of transmissivities in LAN aquifer. To determine the distribution of the transmissivity in LAN aquifer, it would be required to transform the observed heads at the pilot points into transmissivities. Therefore, three procedures wire tackled for the identification of the spatial distribution of the hydrological parameters; geostatistical estimate of the parameter field on the basis of known well point, heads reconstructed by a numerical model, and modification of the values at pilot points by a minimization algorithm. The variogram of Kriging has been applied to a total of 258 transmissivity value in attempt to quantify their distribution of LAN aquifer. Variogram of the observed and optimized transmissivities at pilot points are adapted to the exponential form. So, it is fitted by theoretical one with coefficients of w=0.623, a=2.743. Values of head obtained through numerical analysis are adjusted to the observed values so that heads have been transformed completely into the transmissivities at the observation wells. The procedure represented contour map of the estimated transmissivities and the calculated head.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.3
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• pp.217-227
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• 2002

Geostatistical methods were used for the groundwater flow analysis on the ${\bigcirc}{\bigcirc}$ tunnel area. Linear regression analysis shows that the topographic elevation and ground water level of this area have very high correlation. Groundwater-level contour maps produced by ordinary kriging and cokriging have little differences in mountain areas. But, comparing two maps on the basis of an elevation contour map, a groundwater-level contour map using cokring is more accurate. Analyzing the groundwater flow on two groundwater-level contour maps, the groundwater of study area flows from the north-west mountain areas to near valleys, and from the peak of the mountain to outside areas. In the design steps, the groundwater-level distribution is reasonably considered in the tunnel construction area by cokriging approach. And, geostatistics will provide quantitative information in the unknown groundwatrer-level area.

• Geotechnical Engineering
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• v.10 no.1
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• pp.19-26
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• 1994

In this paper, the application of the rock classification method based on indicator kriging and the cost of errors, which can incorporate qualitative data, was presented. In particular, the binary classification of rock masses was considered. To this end, a simplified RMR system was used. Since most of subjectivity in this analysis occur during the estimation of loss functions, a sensitivity analysis of loss functions was performed. Through this research, it was found out that an expected cost of errors could successfully be used as an indication for how well a sampling plan was designed. In certain conditions, qualitative data can be more economical than quantitative data in terms of expected costs of errors and sampling costs. Therefore, an additional sampling should be carefully determined depending upon the surrounding geologic conditions and its sampling cost. The application method shown in this paper can be useful for more systematic rock classifications.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.2
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• pp.101-111
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• 2004

In order to guarantee the stability of a tunnel and its optimum design, it is very important to obtain enough ground investigation data. In realty, however, it is not the case due to the limitation of measuring spatially distributed data and economical reasons. Especially, there are regions where drilling is impossible due to civil appeal and mountainous topology, and it is also difficult to estimate rock mass classes quantitatively with only geophysical exploration data. In this study, therefore, 3 dimensional multiple indicator kriging (3D-MI kriging), which can incorporate geophysical exploration data and drill core data off a tunnel center line, is proposed to cope with such problems. To this end, two dimensional mutiple indicator kriging, which is one of the geostatistical techniques, is extended for three dimensional analysis. Also, the proposed 3D-MI kriging was applied to determine the rock mass classes by RMR system for the design of a Kyungbu express rail way tunnel.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.849-862
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• 2017

The increased frequency of meteorological disasters has been observed due to increased extreme events such as heavy rainfalls and flash floods. Numerous studies using high-resolution weather radar rainfall data have been carried out on the hydrological effects. In this study, a conditional merging technique is employed, which makes use of geostatistical methods to extract the optimal information from the observed data. In this context, three different techniques such as kriging, inverse distance weighting and spline interpolation methods are applied to conditionally merge radar and ground rainfall data. The results show that the estimated rainfall not only reproduce the spatial pattern of sub-hourly rainfall with a relatively small error, but also provide reliable temporal estimates of radar rainfall. The proposed modeling framework provides feasibility of using conditionally merged rainfall estimation at high spatio-temporal resolution in ungauged areas.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.3
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• pp.133-139
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• 1999

The geostatistical method Kriging is used to estimate the areal distributions of the depth to the water table and the altitude of the water table measured from the sea level. A northern part of the city of Pohang, Kyeong-Buk, Korea has been chosen and the digital map of the area with 1:5,000 scale from the National Geographic Information System (NGIS) project by National Geographic Institute has bun used to reproduce the ground surface distribution. The water table depth appears to be in the range between 7 m and 9.5 m except a few localities where mountain tops exist and the use of groundwater for agicultural purposes is believed to be heavy. The overall distribution of the water table altitude shows a monotonic gradual decrease from the west to the east (seaward direction from the inland) and to the south with maximum rate approximately at 90 m over 6 km in horizontal distance and indicates that the groundwater is moving several meters per day there.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.586-597
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• 2022

In this study, a model was developed for the estimating the locational thickness information of the upper clay layer to be used for the consolidation vulnerability evaluation in the Nakdong river estuary. To estimate ground layer thickness information, we developed four spatial estimation models using machine learning algorithms, which are RF (Random Forest), SVR (Support Vector Regression) and GPR (Gaussian Process Regression), and geostatistical technique such as Ordinary Kriging. Among the 4,712 borehole data in the study area collected for model development, 2,948 borehole data with an upper clay layer were used, and Pearson correlation coefficient and mean squared error were used to quantitatively evaluate the performance of the developed models. In addition, for qualitative evaluation, each model was used throughout the study area to estimate the information of the upper clay layer, and the thickness distribution characteristics of it were compared with each other.