Geo-spatial Multi-resolution Data Structure Vertical Slices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Three-dimensional geo-spatial data storage using quadtrees results in empty nodes at upper levels, leading to increased indexing and parsing overheads without providing useful data, as these data structures are not optimized for three-dimensional information representation.
Innovation Solution
A geo-spatial multi-resolution data structure with vertical slices is used to store three-dimensional data, allowing for recursive traversal based on coordinates within a view frustum, minimizing overheads by balancing data access granularity with the data structure's addressing scheme.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a geo-spatial quadtree data structure is used to store three-dimensional information, then two-dimensional geographical data can be stored efficiently, but empty nodes appear at upper levels increasing indexing and parsing overheads
Solution Approach 1:
The patent extends the two-dimensional quadtree structure to a three-dimensional octree structure by adding a vertical dimension. Each node in the octree represents a cubic volume divided into eight child cubes, allowing efficient storage and indexing of three-dimensional geographical data without creating empty nodes at upper levels, thus resolving the contradiction between storage efficiency and indexing overheads.
2Adaptability or versatility
If upper levels of octree contain empty nodes to represent three-dimensional space, then three-dimensional information can be stored, but indexing overheads increase without providing helpful data
Solution Approach 1:
The patent segments the three-dimensional space into hierarchical cubic volumes, where each node represents a specific vertical slice or layer of the octree. This segmentation allows the system to store three-dimensional information efficiently while avoiding empty nodes by only creating nodes that contain actual data, thus reducing indexing structure complexity while maintaining adaptability.
3Productivity
If vertical slices are used to balance data access granularity, then data retrieval efficiency improves, but data structure complexity increases
Solution Approach 1:
The patent implements dynamic node creation and traversal in the octree structure, where nodes are created only when needed based on the query and vertical slices are dynamically selected. This dynamic approach allows efficient data retrieval by balancing the granularity of data access with the actual data distribution, reducing unnecessary structure complexity while maintaining high retrieval efficiency.
Data Source
AI summary
Embodiments provide a system and method for height based indexing of data. In an embodiment, the present invention parses indexed data by (1) storing a geo-spatial multi-resolution data structure that represents a three dimensional environment, where at least a portion of the three dimensional environment lies within a view frustum; (2) traversing recursively the geo-spatial multi-resolution data structure, where the traversal is based on a range of coordinates that lie within the view frustum; and (3) extracting the indexed data from at least one vertical slice of at least one node of the geo-spatial multi-resolution data structure, where the extracted indexed data is displayed in the view frustum.