Spatial query optimization should be the focus of attention in spatial area. Since relational optimizer is unsuitable for dealing with spatial data

spatial systems should have their own cost model and optimizer. In this paper

a spatial query optimization system—FQPro was presented. After the overview of general phrases of spatial query optimization

we put the emphasis on cost model

calculation of predicate costs and plan costs. In particular

we give a detailed introduction of the cost model based on R-tree. Similar to relational systems

FQPro defines a set of formula for predicate costs and predicate selectivity respectively. They are used in G/SQL. On top of these formulas

the idea and algorithm for forming the optimum execution plan is defined. Concluding this paper are some issues that should be the concerns of research on spatial optimization

primarily the cost model and the extensible system architecture. Also

this paper summarizes the challenges and opportunites facing spatial query processing in the end.