Gridded predictions

Constructing the grid is the hard part done. You can now compute kriged estimates over the grid using the variogram model from before (v_model) and the grid of SpatialPixels.

The spatial pixel grid of the region, spgrid, and the variogram model of pH, v_model have been pre-defined.

Use kriging to predict pH in each grid rectangle throughout the study area.
- Call krige().
- The formula and input data are already specified.
- Pass spgrid as the new data to predict.
- Pass the variogram model to the model argument.
Calculate the probability of alkaline samples in each grid rectangle.
- The mean of the predictions is the var1.pred element of ph_grid.
- The variance of the predictions is the var1.var element of ph_grid. Take the square root to get the standard deviation.
Plot the alkalinity in each grid rectangle.
- Call spplot().
- Pass the alkalinity column to the zcol argument as a string.

Take Hint (-30 XP)

Exercise

Gridded predictions

Instructions