We present a strategy for geographically distributed spatial query optimization that involves multiple sites. Previous work in the area of geographically distributed spatial query processing and optimization focused only on strategies for performing spatial joins and spatial semijoins, and geographically distributed spatial queries that only involve two sites. We propose a strategy for optimizing a geographically distributed spatial query, which uses spatial semijoins and can involve any number of sites in a geographically distributed spatial database. It identifies and initiates spatial semijoins from the smaller spatial relations in order to reduce the larger spatial relations. By doing so, the data transmission and I/O costs are significantly reduced. We compare the performance of our strategy against the naive approach of shipping entire spatial relations to the query site. We find that our optimized strategy minimizes the data transmission cost and I/O cost in all cases, and significantly in specific situations. In addition, the CPU cost is not significantly affected by our strategy.