Geographic feature expansion is a common task in Geographic Information Systems (GIS). Identifying and integrating geographic features is a challenging task since many of their spatial and non-spatial properties are described in different sources. We tackle this expansion problem by defining semantic footprints as a measure of similarity among features. Furthermore, we propose three quantifiers of semantic similarity: spatial, dimensional, and ontological affinity. We show how these measures dilute, concentrate, harden, or concede the feature space, and provide useful insights into the semantic relationships of the spatial entities. Experiments demonstrate the effectiveness of our approach in semantically associating the most appropriate spatial features.