This paper aims to improve locality of references by suitably choosing array layouts. We use a new definition of spatial reuse vectors that takes into account memory layout of arrays. This capability creates two opportunities. First, it allows us to develop an array restructuring framework based on a combination of hyperplane theory and reuse vectors. Second, it allows us to observe the effect of different array layout optimizations on spatial reuse vectors. Since the iteration space based locality optimizations also change the spatial reuse vectors, our approach allows us to compare the iteration-space based and data-space based approaches in terms of their effects on spatial reuse vectors. We illustrate the effectiveness of our technique using an example from the BLAS library on the SGI Origin distributed shared-memory machine.