Moving Window Kriging (Geostatistical Analyst)

ArcGIS Pro 3.4 | | Help archive

Available with Geostatistical Analyst license.

Summary

Recalculates the Range, Nugget, and Partial Sill semivariogram parameters based on a smaller neighborhood, moving through all location points.

Learn more about how Moving Window Kriging works

Usage

  • The geostatistical model source is either a geostatistical layer or a geostatistical model (XML) representing a kriging model other than empirical Bayesian kriging.

  • The input dataset must contain more than 10 points for the tool to execute. However, the tool is most effective with large datasets that have nonstationary trends.

  • In Python scripting, the GeostatisticalDatasets ArcPy class will be useful for populating the Input dataset(s) parameter.

  • For data formats that support Null values, such as file geodatabase feature classes, a Null value will be used to indicate that a prediction could not be made for that location or that the value should be ignored when used as input. For data formats that do not support Null values, such as shapefiles, the value of -1.7976931348623158e+308 is used (this is the negative of the C++ defined constant DBL_MAX) to indicate that a prediction could not be made for that location.

Parameters

LabelExplanationData Type
Input geostatistical model source

The geostatistical model source to be analyzed.

File; Geostatistical Layer
Input dataset(s)

The name of the input datasets and field names used in the creation of the output layer.

Geostatistical Value Table
Input point observation locations

Point locations where predictions will be performed.

Feature Layer
Maximum neighbors to include

Number of neighbors to use in the moving window.

Long
Output feature class

Feature class storing the results.

Feature Class
Output cell size
(Optional)

The cell size at which the output raster will be created.

This value can be explicitly set in the Environments by the Cell Size parameter.

If not set, it is the shorter of the width or the height of the extent of the input point features, in the input spatial reference, divided by 250.

Analysis Cell Size
Output surface raster
(Optional)

The prediction values in the output feature class are interpolated onto a raster using the Local polynomial interpolation method.

Raster Dataset

Licensing information

  • Basic: Requires Geostatistical Analyst
  • Standard: Requires Geostatistical Analyst
  • Advanced: Requires Geostatistical Analyst

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