Traditional storage strategy of raster data cannot meet the demands of coarse-grained data processing under the distributed computing environment and has low efficiency when dealing with calculations for gigantic raster data. A storage strategy of raster tile data was presented on the basis of the storage characteristics of distributed file system. It also took the calculation characteristics of spatial analysis operators of map algebra into consideration, which uses raster tile as processing unit during map and reduce stage. The storage strategy was implemented by the following steps. Firstly raster data were divided into raster tiles. Then these tiles were compressed and organized by a special sequence in order to be transferred to Hadoop distributed file system. Finally input and output file interfaces were re-implemented to meet the data access requirements of map and reduce stage. The strategy was tested and verified by the distributed calculation process of local map algebra operators. Theoretical analysis and experimental results show that this strategy can significantly improve the processing speed of space analysis operators.