Most spatial operations are of high computational complexities. The existing approaches for achieving better performance in spatial data processing include using faster processors and larger main memories, employing multiprocessor systems and parallel computing technology, and/or developing sophisticate algorithms. With the approaches, the price paid for better performance is higher development costs. In this research, we present a different approach for improving spatial operation performance. Our approach is based on better use of the processor cache memory. It may save computing time by 10% to 50%. It does not require upgrading hardware nor re-designing processing algorithms. Faster processing is achieved by simple re-structuring of programs and data. In this Thesis, we describe how cache performance may impact data processing, discuss why better cache strategies can improve spatial operation performance, and describe the techniques we used, and analyze some experimental results.