CAST: Caret Applications for Spatio-Temporal models

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Supporting functionality to run ‘caret’ with spatial or spatial-temporal data. ‘caret’ is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using ‘caret’. To decrease spatial overfitting and to improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to spatial or spatio-temporal model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models.

Note: The developer version of CAST can be found on The CRAN Version can be found on

The figure shows a very simple workflow for a spatial prediction mapping workflow, indicating which function in CAST can be used in the different steps to support the spatial prediction.

Package Website


Scientific documentation of the methods

Spatial cross-validation

Spatial variable selection

Area of applicability

Applications and use cases