Simple Kriging interpolation

Instructions for use

  • The data used in the Simple Kriging method should conform to the assumption that the data changes are normally distributed.
  • Simple Kriging is also one of the commonly used Kriging interpolation methods, which assumes that the expectation (average) of the field values used for interpolation is known by some constant.
  • Simple Kriging assumes that the distribution of sample points tends to be second-order stationary, that is, the distribution of variables in a local area will not change because of the displacement of a spatial point.
  • Simple Kriging interpolation method is not suitable for interpolation of sample data with local trend.

Function Entry

  • Spatial Analysis tab-> Raster Analysis group-> Interpolation Analysis-> Simple Kriging.
  • Toolbox-> Raster Analysis-> Interpolation Analysis-> Simple Kriging. (iDesktopX)

Parameter Description

  • Set public parameters for Interpolation Analysis, including Source Data, Bounds, Result Data, and Environment Settings. For the settings of public parameters such as source data, Bounds, and Result Data, please refer to Public Parameter Description .
  • Set the sample point search method. Fixed Count and Fixed Radius are supported. See: Kr Krügin interpolation for a detailed description of these two lookup methods.

    • Fixed Count: indicates to interpolate by using a fixed number of sample values within the maximum radius.

    • Max Radius: Enter the size of the radius to use for Fixed Count. The default value is 0, which means to use the maximum radius to find.
    • Find Points: Enter the number of points to use for Fixed Count. The default point is 12.

    Fixed Radius: All points within the search radius are involved in the interpolation operation.

    • Search radius: Enter the size of the set search radius. The default lookup radius is 1/5 of the larger value of the length or width of the range of the Dataset participating in the Interpolation Analysis. All the sampling points within the radius range shall participate in the interpolation operation.
    • Minimum number of points: Enter the minimum number of points to be used for Fixed Count. The default is 5 points. When the number of points in the neighborhood is less than specified minimum, the lookup radius increases until it can contain the minimum number of points entered. The maximum value is 12.
  • Other Parameters: includes parameters such as semivariogram type, Rotation angle, average value, sill value, autocorrelation threshold value, nugget effect value, etc.

    Semivariogram: Support spherical function, Exponential and Gaussian semivariogram. Which model to use depends on the Spatial Autocorrelation of the data and the prior knowledge of the data phenomena. Use Exponential by default.

    • Rotate: The angle by which each lookup neighborhood is rotated counterclockwise relative to the horizontal. The default is 0 degrees.

    Average value: The default value is the average value of the interpolation field attribute value, that is, the sum of the interpolation field values of the sampling points divided by the number of sampling points. You can also enter it by yourself.

    Abutment value: The vertex value reached by the semivariogram, that is, the value at which the semivariogram intersects the Y axis at a distance (X axis) of 0. The default is 0.

    Autocorrelation threshold: The distance at which the semivariogram reaches the sill value, that is, the corresponding value of the X axis. The default value is 0.

    Nugget Effect Value: The value at which the semivariance function intersects the Y axis at H = 0 (X axis). The default is 0.

    See Kr Krügin interpolation for the relationship between the sill value, the autocorrelation threshold, and the nugget effect.