Abstract: Qualitative spatial reasoning (QSR) is promising for applications in artificial intelligence and other fields. Much research work bas been done on single spatial relation aspect, while little research focused on integration of two or more aspects. This does not accord with the real world applications, where several aspects are usually involved together. Since different aspects of space are often dependent, it is needed to establish more elaborate formalisms that combine different types of information. The researches on combining topology and distance are not sufficient now. And the model which is tractable in basic relations and easy to implement in GIS is lacking. An extensional topology relation model, BERCC, is proposed based on RCC theories. Its main idea is to improve express ability by using the topological relation of buffers. Some distant information is included in the model. The weak composition table of BERCC is deduced. The basic relations of BERCC are proved to be tractable. The tractable subset of BERCC including basic and full relations is given. A constraint satisfaction reasoning algorithm of BERCC is implemented. Finally, an experimental system is developed with the above theories and methods. The correctness and practicability of the model and the algorithm are validated by the system.