Simple Kriging
Feature Description
- The input data for Simple Kriging should conform to the assumption of normal distribution.
- Simple Kriging is one of the commonly used Kriging interpolation methods, which assumes the expectation (mean value) of the interpolation field is a known constant.
- Simple Kriging assumes sample points follow second-order stationarity, meaning the variable distribution in local areas remains unchanged under spatial displacement.
- This method is not suitable for interpolating sample data with local trend patterns.
Parameter Description
| Parameter | Default Value | Description | Parameter Type |
|---|---|---|---|
| Source Dataset | The point dataset requiring interpolation analysis | DatasetVector | |
| Interpolation Field | Field storing numerical values (elevation, precipitation, etc.) for interpolation. Text-type fields are unsupported. | String | |
| Scaling Ratio | 1.0 | Multiplies source field values before interpolation to scale results. E.g., ratio=2 produces ~2x raster values compared to ratio=1. Typically set to 1. | Double |
| Target Datasource | Datasource for storing result dataset | Datasource | |
| Result Dataset Name | Name of the output dataset | String | |
| Resolution | 0.0 | Spatial resolution of output raster (ground unit per pixel), matching dataset units. | Double |
| Pixel Format | Storage format for raster pixels: 1-bit unsigned, 16-bit, 32-bit, single/double precision float. | PixelFormat | |
| No Value | 0.0 | Value representing null/nodata in output dataset. | Double |
| Search Method | No Search | Point selection mode for interpolation: Variable Length Search, Fixed Length Search, or Block Search. | SearchMode |
| Expected Points (Optional) |
0 | Desired number of points to participate in interpolation | Integer |
| Search Radius (Optional) |
0.0 | Radius for locating interpolation points | Double |
| Max Search Points (Optional) |
0 | Maximum points to use in Block Search mode | Integer |
| Max Points per Block (Optional) |
0 | Maximum points per block in Block Search mode | Integer |
| Variogram Type | Exponential Function | Semi-variogram model type: Spherical Function, Exponential Function, or Gaussian Function. Selection depends on spatial autocorrelation and prior knowledge. Default: Spherical. | VariogramMode |
| Sill | 0.0 | Maximum value of semi-variogram where it stabilizes (Y-intercept). Default: 0. | Double |
| Range | 0.0 | Distance (X-axis) at which semi-variogram reaches sill. Default: 0. | Double |
| Rotation Angle (Optional) |
0.0 | Counterclockwise rotation angle of search neighborhood relative to horizontal. Default: 0 degrees. | Double |
| Mean Value (Optional) |
0.0 | Average of interpolation field values (sum divided by sample count). | Double |
| Nugget Effect | 0.0 | Y-intercept of semi-variogram at h=0. Default: 0. | Double |
| Result Bounds (Optional) |
Geographic extent for interpolation analysis. | String |
Output
| Parameter | Description | Parameter Type |
|---|---|---|
| Result Dataset | Raster dataset generated by interpolation | DatasetGrid |