this mapping method represents the variable under study as a continuous process, unconstrained by the borders of geographic units and where sudden transitions between levels of two neighbouring areas are avoided. It provides the variance of the estimated values from the spatial variability of the actual data, for example, a standard error map, and these error maps can be useful to introduce new sample values for analysis.
An interpolation technique for obtaining statistically unbiased estimates of surface elevations from a set of control points. Pronounced creeging.
An interpolation procedure used to estimate a variable at unsampled locations using weighted sums of the variable at neighboring sample points. The procedure is designed to minimize the variance of the estimation errors. As a meteorological example, kriging can be used for two-dimensional spatial interpolation of irregularly spaced observational data onto a uniform set of grid points to provide input for a numerical forecasting model.
(named after D. G. Krige) - a suite of interpolation techniques that use regionalized variable theory to incorporate information about the stochastic aspects of spatial variation when estimating interpolation weights.
An interpolation technique based on the premise that spatial variation continues with the same pattern.
an interpolation method that minimises the estimation error in the determination of mineral resources
Method of interpolating point data to a grid. Uses statistical theory and a multi-step approach.
A weighted-moving-average interpolation method where the set of weights assigned to samples minimizes the estimation variance, which is computed as a function of the variogram model and locations of the samples relative to each other, and to the point or block being estimated.
A form of statistical modelling that interpolates data from a known set of sample points to a continuous surface.
A form of statistical modeling used in estimating resources that interpolates data from a known set of sample points, such as drill-assay results.
an optimized interpolation technique (named after Dr. D. G. Krige) that uses information about the stochastic (random, local) aspects of spatial variation.
Interpolation technique to obtain statistically unbiased estimates of field characteristics from a set of neighboring points.
A spatial interpolation technique which was originally developed in the mining industry.
A geostatistical technique, which interpolates concentration values for locations between sampling points.
Kriging is a geostatistical method of point estimation which utilizes a variogram model for the given data set. Kriging calculates the weights to be given to each data point used in the estimation in order to provide the smallest possible error of estimation in average.
A technique for spatial interpolation that captures correlations of events. Assumes the joint distribution of spatially distributed measurements is Gaussian. The technique has its roots in Bayesian statistics.
Geostatistical method for generating residuals for remote sensed points for which you don't have field data
an interpolation method for obtaining stastically unbiased estimates for field attributes (yield, nutrients, elevation) from a set of neighboring points.
A geostatistical estimation method that gives the best unbiased linear estimates of point values or of block averages.
Kriging is a regression technique used in geostatistics to approximate or interpolate data. The theory behind interpolation by Kriging was developed by the French mathematician Georges Matheron based on the Master's thesis of Daniel Gerhardus Krige, the pioneering plotter of distance-weighted average gold grades at the Witwatersrand reef complex. The English verb is to krige and the most common adjective is kriging.