A large proportion of the information can be regarded as spatial data which is spatial position related. For accessing spatial databases, different query specification techniques have been proposed. But traditional query methods are tedious and cannot realize fuzzy query. A content-based spatial data retrieval system is presented to afford users a sketch interface which has the ability to accept fuzzy retrieval. Firstly the retrieval algorithm builds the spatial topological vector by refining the 9-intersection model metrically. Then the independent topological relations are extracted by training ICA assisted fuzzy SVMs, which can remove redundancy among the binary relations and reduce the dimension in complex spatial scene. In query processing the
model is referenced, and the similarity is calculated by cosine distance function on the weight vectors of the query scene and each of spatial scenes in database. The experimental results show the recall factor and precision factor are improved compared with the query method without ICA and SVM.