Spatial and temporal granularity can be understood as parameters of context restricting the set of accessible objects in a context. Starting from the idea that this selection process depends to a large extent on the relation between the grain-size of the context and the local extension of the objects, the granularity of a context is in this article formalised as a class of possible sizes in the context. This formalisation is shown to be in accordance to well-known mathematical foundations on perceptual classification. An example for the case of temporal granularity illustrates how the introduction of new elements into a context may result in a more or less smooth shifting of the granularity leading to a classification of four different types of change of granularity. The results can be applied in a wide range of fields, e.g. in research on contextual reasoning and natural language understanding.