An important concern in the design of a publish/subscribe system is its expressiveness, which is the ability to represent various types of information in publications and to precisely select information of interest through subscriptions. We present an enhancement to existing content-based publish/subscribe systems with support for a 2D spatial data type and eight associated relational operators, including those to reveal overlap, containment, touching, and disjointedness between regions of irregular shape. We describe an algorithm for evaluating spatial relations that is founded on a new dynamic discretization method and region-intersection model. In order to make the data type practical for large-scale applications, we provide an indexing structure for accessing spatial constraints and develop a simplification method for eliminating redundant constraints. Finally, we present the results of experiments evaluating the effectiveness and scalability of our approach.