By examining data reuse patterns of four array-intensive embedded applications, we found that these codes exhibit a significant amount of inter-nest reuse (i. e., the data reuse that occurs between different nests). While traditional compiler techniques that target array-intensive applications can exploit intra-nest data reuse, there has not been much success in the past in taking advantage of internest data reuse. In this paper, we present a compiler strategy that optimizes inter-nest reuse using loop (iteration space) transformations. Our approach captures the impact of execution of a nest on cache contents using an abstraction called footprint vector. Then, it transforms a given nest such that the new (transformed) access pattern reuses the data left in cache by the previous nest in the code. In optimizing inter-nest locality, our approach also tries to achieve good intra-nest locality. Our simulation results indicate large performance improvements. In particular, inter-nest loop optimization generates competitive results with intra-nest loop and data optimizations.