Information given in topographic map legends or in GIS models is often insufficient to recognize interesting geographical patterns. Some prototypes of GIS have already been extended with a knowledge-base and some reasoning capabilities to support sophisticated map interpretation processes. Nevertheless, the acquisition of the necessary knowledge is still an open problem to which machine learning techniques can provide a solution. This paper presents an application of first-order rule induction to pattern recognition in topographic maps. Research issues related to the extraction of first-order logic descriptions from vectorized topographic maps are introduced. The recognition of morphological patterns in topographic maps of the Apulia region is presented as a case study.