Interpolation of spatial data is a very general mathematical problem with various applications. In geostatistics, it is assumed that the underlying structure of the data is a stochastic process which leads to an interpolation procedure known as kriging. This method is mathematically equivalent to kernel interpolation, a method used in numerical analysis for the same problem, but derived under c...

heavy metal contamination has been and continues to be a worldwide phenomenon that heavy metals in the soil have an effect on environment and food quality, and may threaten human health. no information is currently available on the distribution pattern of heavy metals concentration in soils of golestan province. the objective of this research was to determine the spatial distribution of cd, as,...

Variograms are used to describe the spatial variability of environmental variables. In this study, the parameters that characterize the variogram are obtained from a variogram in a different but comparably polluted area. A procedure is presented for improving the variogram modelling when data become available from the area of interest. Interpolation is carried out by means of a Bayesian form of...

High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used theModerate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuousmaps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were d...

The Kriging method is an interpolation scheme that can be used for modeling deter-ministic computer analyses as the realization of a stochastic process. The technique has been recognized as an alternative to the traditional Response Surface method in generating approximation models of computationally expensive CFD analyses. This is due to its ability to interpolate sample data and to model a fu...

It is vital to accurately map the spatial distribution of precipitation, which widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. This study aimed reveal seasonal, long-term average precipitation Euphrates Basin with various interpolation methods. For this reason, Simple Kriging, Ordinary Universal CoKriging, Empirical Bayesian Radial Basis Functio...

A practical problem in spatial statistics is that of constructing spatial sampling designs for environmental monitoring networks. Among the several purposes for which a monitoring network may be designed for, there is that of interpolation. In this paper, a criterion for spatial designs that emphasize the utility of the network for spatial interpolation of a random field X is discussed. Within ...

Subsurface models are generally built from both subjective interpretation and mathematical interpolation/extrapolation techniques. These models are therefore uncertain, but their uncertainty is rarely expressed in a geological forecast. In this paper, an evaluation method of geological uncertainties related to 3-D subsurface models is proposed and tested on a real case. This method is based on ...