With the rapid development of space survey technology, GIS is facing a challenge of fast growing size on spatial data and complexity of spatial analysis algorithm. Traditional serial spatial analysis method isn't able to deal with this condition well. High performance computer and new computing methods provide an innovative way for spatial data processing and analysing problem. Remote sensing data processing is data-intensive and an ideal domain to use parallel computing, but vector data operation is computing-intensive which needs more computing ability. In this paper, a distributed spatial analysis framework based on MySQL spatial and MPI is described. Parallel spatial vector data mean is explored in kind of cluster way. This framework uses MySQL spatial cluster to store and manage GIS data which can resolve the problem about fault-tolerant and concurrent access for the same data block. MPI is good at passing messages in distributed network nodes, so it's not necessary to control telecom between nodes manually. Task management and distribution use prior queue to achieve load balance and fault-tolerant through monitoring the status of cluster. Finally, a parallel polygon overlay operation is experimented on this distributed system to test the performance of the cluster. The strategy of parallel Overlay operation is in a pipeline way, each node gets a part set of the polygons in the overlaid layers. And this method got relative better speedup than the serial overlay operation.