Spatial Topology Validation via Line Segment Decomposition
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Solution Overview
Problem
Detecting and correcting topological errors in large spatial datasets, such as topographic map databases, is a time-consuming process due to the need for repeated spatial queries and adjacency analysis, which can be slow and inefficient, especially in datasets with hundreds of millions of features.
Innovation Solution
Decomposing feature geometries into line segments for coordinate vector tests, creating new database structures for validation, and using set difference queries to identify and correct topological errors, allowing for automatic repair and graphical display of modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional spatial query methods are used to validate topological relationships, then validation thoroughness is improved, but processing time increases significantly
Solution Approach 1:
The patent segments the spatial validation process into distinct phases: decomposition of geometries into line vectors, population of database structures with indexed vectors, and execution of set difference queries. This segmentation allows each phase to be optimized independently, reducing overall processing time while maintaining validation thoroughness.
Solution Approach 2:
The patent performs preliminary decomposition of all feature geometries into line vectors and pre-populates database structures with indexed vectors before validation queries are executed. This preliminary action organizes the data in advance, enabling faster validation queries without compromising the thoroughness of topological relationship checking.
2Measurement precision
If feature-based spatial searches are performed for each map feature, then topological error detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent extracts the essential topological validation requirements from complex feature-based spatial searches. By decomposing geometries into line vectors and using set difference queries on indexed database structures, it extracts only the necessary topological relationships without performing comprehensive feature-by-feature spatial analyses, thereby reducing computational complexity while maintaining error detection accuracy.
Solution Approach 2:
The patent replaces the mechanical process of feature-based spatial searches with a more efficient database query mechanism. Instead of performing repeated spatial queries and adjacency analyses, it substitutes this with set difference queries on pre-indexed line vector databases, significantly reducing computational complexity while preserving topological validation accuracy.
3Reliability
If comprehensive topological validation is performed on large datasets, then data integrity is improved, but processing efficiency decreases
Solution Approach 1:
The patent changes the fundamental parameters of the validation approach by transforming geometries into line vectors and using set difference operations on indexed databases. This parameter change enables comprehensive topological validation of large datasets to be performed efficiently, maintaining data integrity while improving processing efficiency through optimized data representation and query mechanisms.
Data Source
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AI summary
The present invention is concerned with automatically validating spatial features of a spatial dataset. The solution is built upon a database server which performs a decomposition of the features' geometries into line segments, after which, sets of line segments are compared to detect errors in the dataset . The decomposition of features geometries into line segments results in a reduction of processing time with a simultaneous increase of precision. The method not only generates new intermediate database structures for detection of topological errors but is also complemented by a clearance process that can lead to the automatic repair of topological errors. The clearance process identifies topological errors and provides modifications to the previously identified line segments such that a modified set of line segments overcomes the conditions that led to the error state. The modifications can be displayed as a graphical overlay above the region of the topological error. The changes to the data set can be applied automatically after displaying them as an overlay for a predefined amount of time.