kriging - [spatial statistics (use for geostatistics)] An interpolation technique in which the surrounding measured values are weighted to derive a predicted value for an unmeasured location.
Kriging developed by Georges Matheron, as the "theory of regionalized variables", and D.G. Krige as an optimal method of interpolation for use in the mining industry
- the basis of this technique is the rate at which the variance between points changes over space ...
Kriging is a group of geostatistical techniques to interpolate the value of a random field (e.g. the elevation Z of the landscape as a function of the geographic location) at an unobserved location from observations of its value at nearby locations.
GIS Dictionary > kriging
Definitions for GIS terms related to operations such as analysis, GIS modeling and web-based GIS, cartography, and Esri software.
Kriging techniques determine window configuration and weighting factors as a function of the spatial autocorrelation in the sample set.
Of the methods which did not use elevation as ancillary information, ~ was most visually plausible. ~ gave better results than optimal inverse distance when data were anisotropic.
The co-~ uses beside semivariograms for each variable also cross-variograms for the variable couples. Let us consider the simple case of two variables. We have n sample points of the primary variable and m sample points of the single secondary variable (for simple writing we suppose m=n+1).
An interpolation technique in which the surrounding measured values are weighted to derive a predicted value for an unmeasured location. Weights are based on the distance between the measured points, the prediction locations, and the overall spatial arrangement among the measured points.
~ - A mathematical interpolation method based on the use of a generalized least-squares algorithm. It was first developed for mining applications but is now commonly used for 3-D geographic data processing.
Simple ~ is now the default ~ method; in previous versions, the default was Ordinary ~. The change was made because of the flexibility of the new Multiplicative Skewing normal score transformation.
Mask environment ...
~ p. 212 a geostatistical technique for interpolation that uses information about the spatial autocorrelation in the vicinity of each point to provide 'optimal' interpolation (in the sense of greater use of the information provided by the spatial arrangement). L
Digital elevation models (DEM), triangulated irregular networks (TIN), Edge finding algorithms, Theissen Polygons, Fourier analysis, Weighted moving averages, Inverse Distance Weighted, Moving averages, ~, Spline, ...
Other highly complex interpolation methods exist such as ~. ~A complex geostatistical technique that employs semivariograms to interpolate the values of an input point layer and is more akin to a regression analysis.
This interpolation method is not always appropriate, so there are other methods including Fixed-radius Local Averaging, Inverse Distance Weighted, Trend Surface, Splines, and ~.
These three techniques are Linear interpolation, which effectively runs a straight line between the points with altitude values, the Cubic Spline, which interpolates a smooth curve through the given data points, and Statistical interpolation using ~ semi-variograms.
Image analysis: filters, edge detection, cluster analysis, segmentation
Digital Terrain Analysis: generate geomorphometric indexes, channel networks, profiles, contour lines, ...
Geostatistics: modules for variogram fitting and ~ ...
See also: What is the meaning of Model, Analysis, Interpolation, Information, GIS?