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How to create a prediction map using cokriging?
Use cokriging to produce prediction, probability, quantile, standard error, and standard error of indicators maps under the same conditions as for the other kriging methods. Click the Geostatistical Analyst Wizard button on the Geostatistical Analyst toolbar.
Are there different types of Kriging in Geostatistical Analyst?
The Geostatistical Wizard offers several types of kriging, which are suitable for different types of data and have different underlying assumptions: These methods can be used to produce the following surfaces: The exceptions to this are: There are several components of geostatistical models.
What is the geostatistical Wizard in ArcGIS?
The Geostatistical Wizard is a dynamic set of pages that is designed to guide you through the process of constructing and evaluating the performance of an interpolation model. Choices made on one page determine which options will be available on the following pages and how you interact with the data to develop a suitable model.
Can you use cokriging as a Geostatistical Analyst?
Available with Geostatistical Analyst license. Use cokriging to produce prediction, probability, quantile, standard error, and standard error of indicators maps under the same conditions as for the other kriging methods. Click the Geostatistical Analyst Wizard button on the Geostatistical Analyst toolbar.
Which is the main variable used in cokriging?
Cokriging uses information on several variable types. The main variable of interest is Z 1, and both autocorrelation for Z 1 and cross-correlations between Z 1 and all other variable types are used to make better predictions. It is appealing to use information from other variables to help make predictions, but it comes at a price.
When do you use semivariograms in cokriging?
Semivariograms or covariances (the mathematical forms used to express autocorrelation), cross-covariance (the mathematical form used to express cross-correlation), transformations, trend removal, and measurement error can be used when performing ordinary, simple, or universal cokriging.
How is cokriging used to predict z 1?
Ordinary cokriging attempts to predict Z 1 ( s0 ), just like ordinary kriging, but it uses information in the covariate Z 2 ( s) in an attempt to do a better job. For example, the following figure has the same data that was used for ordinary kriging, only here a second variable is added.