In this article, an approach is presented for the representation and reasoning over qualitative spatial relations. A set-theoretic approach is used for representing the topology of objects and underlying space by retaining connectivity relationships between objects and space components in a structure, denoted, adjacency matrix. Spatial relations are represented by the intersection of components, and spatial reasoning is achieved by the application of general rules for the propagation of the intersection constraints between those components. The representation approach is general and can be adapted for different space resolutions and granularities of relations. The reasoning mechanism is simple and the spatial compositions are achieved in a finite definite number of steps, controlled by the complexity needed in the representation of objects and the granularity of the spatial relations required. The application of the method is presented over geometric structures that takes into account qualitative surface height information. It is also shown how directional relationships can be used in a hybrid approach for richer composition scenarios. The main advantage of this work is that it offers a unified platform for handling different relations in the qualitative space, which is a step toward developing general spatial reasoning engines for large spatial databases.