In recent times, there is a growing interest in both the extension of data mining methods and techniques to spatial databases and the application of inductive logic programming (ILP) to knowledge discovery in databases (KDD). In this paper, an ILP application to association rule mining in spatial databases is presented. The discovery method has been implemented into the ILP system SPADA, which benefits from the available prior knowledge on the spatial domain, systematically explores the hierarchical structure of task-relevant geographic layers and deals with numerical aspatial properties of spatial objects. It operates on a deductive relational database set up by selecting and transforming data stored in the underlying spatial database. Preliminary experimental results have been obtained by running SPADA on geo-referenced census data of Manchester Stockport, UK.