Spatial query processing using generalized filter

Spatial data, ranging from various land information data to different types of environmental data, are typically collected and used by different custo dians. The full benefits of using spatial data can be achieved by combining the data from different sources covering a common region. Due to organizat ional, political and technical reasons, it is unrealistic to physically int egrate the vast amount of spatial data managed by different systems in diff erent organizations. A practical approach is to provide interoperability to support multi-site data queries. In this paper, we study the performance a spect of complex spatial query processing. We propose a framework for proce ssing queries with multiple spatial and aspatial predicates using data from multiple sites. Using a new concept called generalized filter, a query is processed in three steps. First, an aspatial filter that incorporates some conditions derived from spatial predicates is used to find a sat of candida tes, which is a superset of the final query results. Then, the candidates a re manipulated and a refinement step is executed following an optimized can didate sequence. Finally, a post-processing step is used to handle spatial expressions in query results. The focus of this paper is to generate enhanc ed filters in order to minimize the need of transferring and processing com plex spatial data.