Spatial aggregation produces images of coarser resolution (grouping pixels in a grid of coarser resolution and calculating mean values) or of coarser scale (by filtering with low-pass filters). Thereby it is a form of generalization that may improve classification results. Spatial aggregation can be applied after classification to get rid of the salt-and-pepper effect.