Conventional spatial queries, such as range search and nearest neighbor retrieval, involve only conditions on objects based on different selection criteria.Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial predicate and a predicate on their associated texts. The important of spatial database is reflected by the convenience of modeling entities of reality in a geometric manner.Location of restaurants, hotels, hospitals and so on is often represented as points in a map.Currently, the best solution to such queries is based on the IR2-tree.we are interested in a more general form of local search, that is, to search local content on the Web. In our approach, each web page will be first assigned to a few geographical locations according to its content and then spatially indexed in the search engine.A straightforward approach is to treat geographical words which represent location information as common keywords, and to retrieve web pages with specified location names in the same way to keyword matching.To solve the problem, it is necessary to design an efficient index structure that considers both spatial and textual features of web pages. How to efficiently index and search location-specific information is being a key problem for location based search engines