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UNIVERSAL KRIGING
=================
Description
-----------
Parameters
----------
- ``Points[Vector]``:
- ``Attribute[TableField]``:
- ``Create Variance Grid[Boolean]``:
- ``Target Grid[Selection]``:
- ``Variogram Model[Selection]``:
- ``Block Kriging[Boolean]``:
- ``Block Size[Number]``:
- ``Logarithmic Transformation[Boolean]``:
- ``Nugget[Number]``:
- ``Sill[Number]``:
- ``Range[Number]``:
- ``Linear Regression[Number]``:
- ``Exponential Regression[Number]``:
- ``Power Function - A[Number]``:
- ``Power Function - B[Number]``:
- ``Grids[MultipleInput]``:
- ``Grid Interpolation[Selection]``:
- ``Min.Number of m_Points[Number]``:
- ``Max. Number of m_Points[Number]``:
- ``Maximum Search Radius (map units)[Number]``:
- ``Grid Size[Number]``:
- ``Fit Extent[Boolean]``:
- ``Output extent[Extent]``:
Outputs
-------
- ``Grid[Raster]``:
- ``Variance[Raster]``:
See also
---------
Console usage
-------------
::
processing.runalg('saga:universalkriging', shapes, field, bvariance, target, model, block, dblock, blog, nugget, sill, range, lin_b, exp_b, pow_a, pow_b, grids, interpol, npoints_min, npoints_max, maxradius, user_cell_size, user_fit_extent, output_extent, grid, variance)
Available options for selection parameters:
target(Target Grid)
0 - [0] user defined
model(Variogram Model)
0 - [0] Spherical Model
1 - [1] Exponential Model
2 - [2] Gaussian Model
3 - [3] Linear Regression
4 - [4] Exponential Regression
5 - [5] Power Function Regression
interpol(Grid Interpolation)
0 - [0] Nearest Neighbor
1 - [1] Bilinear Interpolation
2 - [2] Inverse Distance Interpolation
3 - [3] Bicubic Spline Interpolation
4 - [4] B-Spline Interpolation
|
