Spatial location retrieval is one of important pretreatment steps in remote sensing data searching. In order to improve the original Ray-algorithm performance and reduce the false alarm rate in retrieving catalogue data from massive remote sensing images

a new hybrid parallel strategy has been proposed based on MPI and OpenMP to implement the Ray-algorithm. First

two improved processing methods have been added to the classical Ray-algorithm to deal with two special cases between the point on the edge of the polygon and the ray intersecting on the endpoint. And then

we use multi-process based on MPI to do parallel computing on a PC cluster in program procedure and multi-threads based on OpenMP to do parallel algorithm implementation in which many threads are started synchronously to deal with each point of the polygon which is in another point or not. The experimental results show that the whole system will reach better speedup when the sum of started threads in all nodes is equal to the optimal threads number of the main node.Compared with serial algorithm

the retrieval time of hybrid parallel algorithm reduced by more than 50% and this algorithm is more efficient. The hybrid parallel strategy based on MPI and OpenMP is better than common serial execution and parallel execution based on MPI and OpenMP respectively. The hybrid parallel mode is generally applicable to the cluster environment parallel programs and it can used to deal with other images processing algorithms with parallel features.