Abstract
In order to improve the efficiency of spatial data access and retrieval performance, an index structure is designed, it solves the problem of low query efficiency of the single index structure when there are large amount of data. Through the establishment of correspondence between the logical records and physical records of the spatial data, the hybrid spatial data index structure is designed based on 2K –tree and R-tree. The insertion, deletion and query algorithm are implemented based on the hybrid tree, and the accuracy and efficiency are verified. The experimental results show that the hybrid tree needs more storage space then R-tree, but with the data volume increasing the storage space needed declining relatively, and the hybrid tree is better than the R-tree in the retrieval efficiency, and with the data volume increasing the advantage is more obvious.
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Wang, Y., Zhu, Y., Sun, H. (2011). Study of Spatial Data Index Structure Based on Hybrid Tree. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_68
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DOI: https://doi.org/10.1007/978-3-642-25661-5_68
Publisher Name: Springer, Berlin, Heidelberg
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