abstract: converting point data to continuous one is the first step in order to use them in scorpan flowchart. for this purpose, different geostatistic methods are available which at present research regression kriging with local variogram was applied. for mapping apparent electrical conductivity at the area covering 72000ha located in ardakan region, 700 readings in horizontal and vertical mod...

Many food products are subjected to quality control analyses for detection of surface residue/contaminants, and there is a trend of requiring more and more documentation and reporting by farmers regarding their use of pesticides. Recent outbreaks of food borne illnesses have been a major contributor to this trend. With a growing need for food safety measures and ―smart applications‖ of insectic...

This paper presents the development and testing of two techniques of texture analysis based on different mathematical tools: the semi-variogram and the Fourier spectra. Three series of experiments are presented where these techniques are compared against a bench mark technique: the Grey-Tone Dependency Matrix. Results, their interpretation and conclusions are presented.

Let Z(s)=(Z1(s),…,Zp(s))t be an isotropic second-order stationary multivariate spatial process. We measure the statistical association between p random components of Z with correlation coefficients and dependence variograms. If two are correlated, information provided by one them can improve other. To capture this association, both within Z(s) across s, we use a cross-variogram. Only robust cro...

In modeling spatial processes, a second-order stationarity assumption is often made. However, for data observed on vast domain, the covariance function varies over space, leading to heterogeneous dependence structure, therefore requiring nonstationary modeling. Spatial deformation one of main methods assuming process has stationary counterpart in deformed space. The estimation poses severe chal...

There are many reasons for the popular use of the isotropic or geometrically anisotropic covariance function and variogram in spatial statistics. A less known reason demonstrated in this paper is that an isotropic or geometrically anisotropic model would be the only choice in certain circumstances, for instance, when the underlying random field is smooth enough.