If urban development plans were just target patterns to be achieved, conventional data structures in GIS would be sufficient. Urban development plans have a strong spatial component, but recent literature in planning emphasizes that plans are about actions and relationships among them. These relationships include interdependence, substitutability, priority, and parthood. In order to support planning, GIScience should devise data structures and queries to support reasoning with these relationships. This paper shows how relationships encoded within each of a set of plans, using a recently developed data model, can be used to infer the relationships of actions among these plans. Simple databases and use cases based on real situations in McHenry County, Illinois are used to demonstrate that these relationships can be encoded and queried. The results demonstrate that previously dis- covered semantic relationships can be used to discover additional relationships across plans, thereby enriching the decision making. The approach provides a systematic way of structuring the information in plans to support making and using plans.