In their article Liao et al. (2006) argued that it is feasible to use national scale daily kriging to estimate ambient air pollution exposure, even in locations where monitoring data are limited. In addition, they argued that national scale kriging is preferable to regional kriging and that automated variogram estimation is preferable to manual. The advocated methodology seems appealing when co...

This study aims to recognize effect of Ordinary Kriging (OK) and Inverse Distance Weighted (IDW) estimation methods for separation of geochemical anomalies based on soil samples using Concentration-Area (C-A) fractal model in Irankuh area, central Iran. Variograms and anisotropic ellipsoid were generated for the Pb and Zn distribution. Thresholds values from the C-A log-log plots based on the e...

Introduction: It is generally accepted that groundwater is one of the most vital sources of water for drinking use in cities and rural areas. The water drawn from these sources should be sanitary, have low soluble substances, and be free of any pathogens and microorganisms. Materials and Methods: In this study, 90 wells were sampled with proper dispersion over the study area to achieve suitabl...

When modelling a large area, models that can take into a count the variation from the general mean in small sub-areas could perform better in prediction than a general model fitted to entire dataset. One method for adjusting the large-area models for such variation is kriging, in which the predictions are corrected with the aid of neighbouring observations. A variogram represents the spatial co...

Four spatial estimation techniques available in commercial computational packages are evaluated and compared, namely: regularized splines interpolation, tension splines interpolation, inverse distance weighted interpolation, and ordinary Kriging estimation, in order to establish the best representation for the shallow stratigraphic configuration in the city of Aguascalientes, in Central Mexico....

Several important forms of robotic environmental monitoring involve estimating a spatial field from comparatively few measurements. A number of researchers use linear least squares estimation techniques, frequently either the geostatistical Kriging framework or a Gaussian Process regression formulation, that provide estimates of quantities of interest at unmeasured locations. These methods enab...