Geospatial Query Indexing Using Ellipsoidal to Flat Coordinate Transformation
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Solution Overview
Problem
Existing geospatial search systems face inefficiencies due to the high computational expense of ellipsoidal geometric calculations and the occurrence of false positives in region queries, particularly when dealing with geographic coordinate systems.
Innovation Solution
A grid-based system that employs a primary index for interior and exterior grid blocks and a secondary index for blocks containing boundaries, transforming ellipsoidal coordinates to flat coordinates to reduce query time and minimize false positives by using a combination of primary and secondary indexes for efficient geospatial query processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ellipsoidal geometric calculations are performed for geospatial queries, then query accuracy is improved, but query time expense increases
Solution Approach 1:
The patent pre-calculates and stores minimum bounding rectangles (MBRs) for all geospatial regions during data insertion. These MBRs are stored in an index structure that allows rapid querying. During query execution, the pre-computed MBRs enable fast filtering without performing expensive ellipsoidal geometric calculations at query time, thus resolving the contradiction between query accuracy and query time expense.
2Device complexity
If a single index structure is used for all geospatial queries, then device complexity is reduced, but query accuracy deteriorates due to false positives
Solution Approach 1:
The patent divides the indexing task into two segments: a primary index using minimum bounding rectangles for fast initial filtering, and a secondary verification step using the actual geospatial region geometry. This segmentation allows the system to use a simple MBR-based index structure while still achieving accurate query results by verifying candidates against the true geometry, thus resolving the contradiction between device complexity and query accuracy.
Data Source
AI summary
A method implemented by a computer with a processor and a memory storing instructions executed by the processor includes receiving a query with a search region and a predicate. The search region is mapped to a set of blocks. For each block in the set of blocks, ellipsoidal geographic coordinates of the search region are transformed to flat coordinates. Results are retrieved from a primary index when the block does not contain a boundary of the search region. Results are retrieved from a secondary index when the block does contain a boundary of the search region. Retrieving results from the secondary index includes processing the boundary and the predicate against the secondary index.