Introduction | Background | How to start | Example of a typical spatio-temporal prediction task | Description of the example dataset | Model training and prediction | Cross validation strategies for spatio-temporal data | The Standard approach: Random k-fold CV | Target-oriented validation | Removing variables that cause overfitting | Area of Applicability | Error profiles | Conclusions | Final notes | Further Reading | Tutorials | Scientific documentation of the methods | Spatial cross-validation | Spatial variable selection | Area of applicability | Applications and use cases

Introduction | Sample data | Prediction area | Spatial random sample | Clustered sample | Distances in geographic space | Accounting for cross-validation folds | Random Cross-validation | Spatial Cross-validation | Why has spatial CV sometimes blamed for being too pessimistic ? | Nearest Neighbour Distance Matching CV | Distances in feature space | Further reading

Introduction | Getting started | Example 1: Using simulated data | Get data | Generate Predictors | Generate Response | Simulate sampling locations | Model training | Prepare data | Train the model | Variable importance | Predict and calculate error | AOA and LPD calculation | AOA for spatially clustered data? | Comparison prediction error with model error | Relationship between the DI/LPD and the performance measure | Example 2: A real-world example | Data and preprocessing | Model training and prediction | Prediction | AOA estimation | Final notes | Further reading

Forward feature selection | Area of applicability | trainDI | AOA for multiple rasters

Introduction | Cross-validation in geographical space | Evaluation of spatial predictive conditions | NNDM LOO CV for small datasets | kNNDM CV for medium and large datasets | Cross-validation in feature space | Further reading