# An overview of kriging model classes

Spatial Analyst のライセンスで利用可能。

The kriging model classes define the kriging method and its parameters that will be used in a kriging interpolation. There are two kriging methods: ordinary and universal.

Ordinary kriging is the most general and widely used of the kriging methods and is the default. It assumes the constant mean is unknown. This is a reasonable assumption unless there is a scientific reason to reject it.

Universal kriging assumes that the spatial variation in z-values is the sum of three components: a structural component (drift), a random but spatially correlated component, and a random noise representing the residual error. The structural component represents a constant trend over the surface. The random noise is assumed to be spatially independent and have a normal distribution. Once the structural effects have been accounted for, the remaining variation is spatially homogeneous such that the z-value difference between input sample points is merely a function of the distance between them as with ordinary kriging.

Class | Description |
---|

KrigingModelOrdinary | Defines the Ordinary Kriging model. The available model types are Spherical, Circular, Exponential, Gaussian, and Linear. |

KrigingModelUniversal | Defines the Universal Kriging model. The available model types are Linear with linear drift and Linear with quadratic drift. |

The following tool uses kriging objects:

このトピックへのフィードバック