Method for managing and querying geo-spatial data using a grid-code-array spatial index

As geospatial data is increasingly massive and complex, large data volume and rich data source query retrieval are among the urgent issues in need of resolution. Spatial indices are widely used to organize data and optimize queries. However, tree-based indices are increasingly difficult to adapt to a high-efficiency query, and the combination of a grid index and space-filling curve can help decrease the dimensions to improve the query efficiency, but can also lead to data redundancy as one object can cover several grids. To solve the aforementioned problems, this paper proposes a method to manage and query data using a grid-code-array spatial index based on a GeoSOT global subdivision model. For the first time, a grid code was organized in a code-array format and an inverted index was constructed on the column of the code-array. By adding a grid-code-array data structure, we verified the feasibility and efficiency and compared the R-tree index in the Oracle Spatial system and the grid index in the ArcSDE geodatabase for Oracle, which are the most widely used. Experimental results showed that the spatial index we proposed has obvious advantages, which could solve the problem of storage redundancy and query results, and effectively improve spatial queries particularly when the data volume is large.