Trend Modeling: First, a deterministic trend model is fitted to the data. This model captures the broad-scale variations in the mean. Residual Modeling: The residuals, or deviations from the trend, are then modeled using a variogram to account for spatial autocorrelation. Prediction: Finally, predictions are made by combining the trend model and the spatial structure of the residuals.
