• Honam Mathematical Journal
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• v.26 no.1
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• pp.87-103
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• 2004

A practical estimation method for groundwater contaminant concentration is introduced. Using geostatistical techniques and symmetry, experimental variograms show significant improved correlation compared with those from conventional techniques. Numrical experiments are performed using a field data set.

• Environmental Analysis Health and Toxicology
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• v.31
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• pp.6.1-6.10
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• 2016

Objectives This study examined the spatial distribution and the extent of soil contamination by heavy metals resulting from primitive, unconventional informal electronic waste recycling in the Agbogbloshie e-waste processing site (AEPS) in Ghana. Methods A total of 132 samples were collected at 100 m intervals, with a handheld global position system used in taking the location data of the soil sample points. Observing all procedural and quality assurance measures, the samples were analyzed for barium (Ba), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn), using X-ray fluorescence. Using environmental risk indices of contamination factor and degree of contamination ($C_{deg}$), we analyzed the individual contribution of each heavy metal contamination and the overall $C_{deg}$. We further used geostatistical techniques of spatial autocorrelation and variability to examine spatial distribution and extent of heavy metal contamination. Results Results from soil analysis showed that heavy metal concentrations were significantly higher than the Canadian Environmental Protection Agency and Dutch environmental standards. In an increasing order, Pb>Cd>Hg>Cu>Zn>Cr>Co>Ba>Ni contributed significantly to the overall $C_{deg}$. Contamination was highest in the main working areas of burning and dismantling sites, indicating the influence of recycling activities. Geostatistical analysis also revealed that heavy metal contamination spreads beyond the main working areas to residential, recreational, farming, and commercial areas. Conclusions Our results show that the studied heavy metals are ubiquitous within AEPS and the significantly high concentration of these metals reflect the contamination factor and $C_{deg}$, indicating soil contamination in AEPS with the nine heavy metals studied.

• The Journal of Engineering Geology
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• v.9 no.2
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• pp.147-159
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• 1999

Geostatistical methods were used for the groundwater flow analysis in a heterogeneous anisotropic aquifer. This study area is located at Sonbul-myeon in Hampyong-gun of Cheonnam Province which is a hydrogeological project area of KORES(Korea Resources Cooperation). Linear regression analysis shows that the topographic elevation and groundwater level of this area have very high correlation. Groundwater-level contour maps produced by ordinary kriging and cokringing have large differences in mountain areas, but small differences in hill and plain areas near the West Sea. Comparing two maps on the basis of an elevation contour map, a groundwater-level contour map using cokriging is more accurate. Analyzing the groundwater flow on two groundwater-level contour maps, the groundwater of study area flows from the high mountain areas to the plain areas near the West Sea. To verify the enffectiveness of geostatistical methods for the groundwater flow analysis in a heterogeneous anisotropic aquifer, the flow directions of groundwater were measured at two groundwater boreholes by a groundwater flowmeter system(model 200 $GeoFlo^{R}$). The measured flow directions of groundwater almost accord with those estimated on two groundwater-level contour maps produced by geostatistical methods.

• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.177-189
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• 2012

Evaluation of three-dimensional ore body modeling has been performed by applying the geostatistical integration technique to multiple geophysical (electrical resistivity, MT) and geological (borehole data, physical properties of core) information. It was available to analyze the resistivity range in borehole and other area through multiple geophysical data. A correlation between resistivity and density from physical properties test of core was also analyzed. In the case study results, the resistivity value of ore body is decreased contrast to increase of the density, which seems to be related to a reason that the ore body (magnetite) includes heavy conductive component (Fe) in itself. Based on the lab test of physical properties in iron mine region, various geophysical, geological and borehole data were used to provide ore body modeling, that is electrical resistivity, MT, physical properties data, borehole data and grade data obtained from borehole data. Of the various geostatistical techniques for the integrated data analysis, in this study, the SGS (sequential Gaussian simulation) method was applied to describe the varying non-homogeneity depending on region through the realization that maintains the mean and variance. With the geostatistical simulation results of geophysical, geological and grade data, the location of residual ore body and ore body which is previously reported was confirmed. In addition, another highly probable region of iron ore bodies was estimated deeper depth in study area through integrated modeling.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.59-64
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• 2005

Although experimental analysis for groundwater sample at wells located systematically are very effective to delineate seawater intrusion region at coastal area, this method is restricted in few wells and time. We have conducted electrical resistivity sounding at 30 points in the study areas to analyze the region of seawater intrusion and found the boundary between salt wedge and fresh water lens from the analysis results of geostatistical method using variogram for one-dimensional inversion results. The methodology adopted in this study would be useful for finding the seawater intrusion region and evaluating quantitatively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.399-401
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• 2003

This paper presents a geostatistical contextual classifier for the classification of remote sensing data. To obtain accurate spatial/contextual information, a simple indicator kriging algorithm with local means that allows one to estimate the probability of occurrence of certain classes on the basis of surrounding pixel information is applied. To illustrate the proposed scheme, supervised classification of multi-sensor remote sensing data is carried out. Analysis of the results indicates that the proposed method improved the classification accuracy, compared to the method based on the spectral information only.

• Journal of Ecology and Environment
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• v.37 no.2
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• pp.53-60
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• 2014

The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran's I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially autocorrelated vegetation consisted of moss, Eriophorum vaginatum, Betula nana, and Rubus chamaemorus. Interpolation maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis. These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution.

• Environmental Engineering Research
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• v.22 no.4
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• pp.369-376
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• 2017

The trend analysis of the study was acquired by selecting multiyear monthly groundwater table data and monitors the wells in each sub-district under the study area. The intention of this research was to analyze the outcome of the non-parametric Mann-Kendall test at greater than the significance level which is 95% of groundwater level in Sylhet. The aptitude is effective at two conjunctures where the confidence bounds are 95% and it meets the estimate line of Sen's. To calculate and assess the spatial differences in the inanition of groundwater table, geostatistical methods was applied based on data from 27 groundwater wells during the period from January 1975 to December 2011 which were obtained from a secondary source, Bangladesh Water Development Board. The geographic information system was used to assess the spatial change in order to find the level of groundwater. Cross-validation errors were found within an advisable level in estimating the groundwater depth with different interpolation models of ordinary kriging methods. Finally, surface maps were generated with the best-fitted model. The southeast region was found highly vulnerable from groundwater level point of view. Northern region was detected highest hazard prone area for diverge groundwater using kriging method.

• Journal of Biosystems Engineering
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• v.29 no.2
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• pp.109-120
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• 2004

To obtain basic information for precision agriculture, spatial variability of rice growth condition was evaluated in 100m ${\times}$100m paddy field. The rice growth condition of four hundred locations in the field were investigated to analyze the spatial variability of their properties ; SPAD, plant length and tiller number. Geostatistical analysis was carried out to examine within-field spatial variability using semivariograms and kriged maps as well as descriptive statistics. Descriptive statistics showed that the coefficient of variation for SPAD, plant length, and tiller number exceeded 5.70 %, suggesting a relatively high variability. Geostatistical analysis indicated a high spatial dependence for all the properties except for the second tiller number. The range of spatial dependence was about 20 m for SPAD, plant length, and tiller number. Based on the results of spatial dependence, kriged maps were prepared for the properties to analyse their spatial distribution in the field. The results reflected the history of field management. In conclusion, the need for site-specific field management and possibility of precision agriculture were demonstrated even in an almost flat paddy field.

• Ecology and Resilient Infrastructure
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• v.4 no.2
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• pp.93-96
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• 2017

Spatial variations of physicochemical and microbiological variables were examined to understand spatial heterogeneity of those variables in intertidal flat. Variograms were constructed for understanding spatial autocorrelations of variables by a geostatistical analysis and spatial correlations between two variables were evaluated by applications of a Cross-Mantel test with a Monte Carlo procedure (with 999 permutations). Water content, organic matter content, pH, nitrate, sulfate, chloride, dissolved organic carbon (DOC), four extracellular enzyme activities (${\beta}-glucosidase$, N-acetyl-glucosaminidase, phosphatase, arylsulfatase), and bacterial diversity in soil were measured along a transect perpendicular to shore line. Most variables showed strong spatial autocorrelation or no spatial structure except for DOC. It was suggested that complex interactions between physicochemical and microbiological properties in sediment might controls DOC. Intertidal flat sediment appeared to be spatially heterogeneous. Bacterial diversity was found to be spatially correlated with enzyme activities. Chloride and sulfate were spatially correlated with microbial properties indicating that salinity in coastal environment would influence spatial distributions of decomposition capacities mediated by microorganisms. Overall, it was suggested that considerations on the spatial distributions of physicochemical and microbiological properties in intertidal flat sediment should be included when sampling scheme is designed for decomposition processes in intertidal flat sediment.