Abstract
In order to meet the needs of load balance and keep the consistency of spatial data shape types and spatial relationships, this paper proposes a grid-aided and STR-Tree-based spatial data partition (GASTRSDP) method to divide vector data. The algorithm implements statistic load balance for the distributed storage of mass spatial data. On the basis of the grid and STR-Tree index, the workflow of the GASTRSDP is firstly introduced. Three methodological issues are then discussed. The results of experiments show that total time consumption of data partition using GASTRSDP is less than that using traditional grid-based algorithm. The GASTRSDP-partitioned-based spatial union is more efficient than other three spatial union procedures. With the same volume of data, the storage cost of GASTRSDP-based index is more than that of grid-based partition method.
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