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Spatial joins are important operations in applications such as Geographic Information Systems Cartography and CAD/CAM Spatial join using existing R-trees is a very useful and popular technique because of both its superior performance and the wide spread implementation of R-trees as spatial index structures This paper describes a new spatial join method called BFRJ (Breadth- First R-tree Join) BFRJ synchronously traverses both R-trees in breadth-first order processing the join computation one level at a time This way an intermediate join index can be created at each level to guide the join process at the next lower level Unlike the limitation of the state-of-the-art depth-first R-tree join method which can only optimize I/O within local sub-trees the breadth-first ordering allows BFRJ to deploy global optimization strategies among all nodes at the next lower level In particular BFRJ optimization strategies include index ordering memory management and buffer management of the intermediate join indices This paper also presents an experimental evaluation of the effect of the proposed optimizations as well as a performance comparison between BFRJ and the state-of-the-art approach Our experimental results indicate that BFRJ with global optimizations can outperform the competitor by a significant margin (up to 50%)