Geospatial Indexing Using Tree Data Structure for Map Feature Fragments
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Solution Overview
Problem
Current geospatial indexing methods are inefficient in storing and retrieving map data, leading to memory overload and slow performance when handling large sets of map data across varying levels of detail, as they store duplicate map feature fragments for each level of detail.
Innovation Solution
A geospatial indexing module uses a tree data structure to store map feature fragments at multiple levels of detail, allowing for efficient retrieval by selecting nodes corresponding to the requested geographic region and level of detail, and employing a bucketing system for non-spatial attribute filtering to provide only relevant data to the client device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If duplicate map feature fragments are stored for each level of detail, then map data can be retrieved at any zoom level, but memory usage increases and performance decreases
Solution Approach 1:
The patent implements a hierarchical tree data structure where map feature fragments are organized in nested levels of detail. Each node in the tree represents a geographic region at a specific zoom level, and child nodes contain refined versions of parent node data. This nesting allows the system to store only essential data at each level rather than duplicate full datasets, reducing memory consumption while maintaining the ability to retrieve appropriate data for any requested zoom level.
Solution Approach 2:
The patent applies local quality by storing map feature fragments with varying levels of detail in different regions of the data structure. High-detail fragments are stored only where needed (at lower zoom levels), while simplified fragments are stored for broader regions (at higher zoom levels). This selective storage strategy reduces overall memory usage by avoiding the storage of high-detail data across all zoom levels, while still providing appropriate detail for each specific retrieval request.
2Reliability
If duplicate map feature fragments are stored for each level of detail, then complete map data is available for retrieval, but retrieval speed decreases due to data redundancy
Solution Approach 1:
The hierarchical tree structure enables efficient retrieval by allowing the system to navigate directly to the appropriate level of detail for the requested zoom level. Instead of searching through redundant duplicate fragments across all levels, the system traverses the nested structure from root to leaf nodes, retrieving only the necessary fragments for the specific zoom level. This reduces retrieval time while ensuring complete and accurate map data is provided.
Solution Approach 2:
The patent extracts and stores only the essential map feature fragments needed for each level of detail in the hierarchical structure. Rather than storing complete duplicate sets at every level, the system extracts and stores representative fragments at each hierarchical level, which can then be efficiently retrieved and rendered. This extraction strategy maintains data completeness for retrieval while significantly improving access speed by eliminating redundant storage and search operations.
3Measurement precision
If all map feature fragments are retrieved and filtered client-side, then accurate filtering is achieved, but processing time and client device load increase
Solution Approach 1:
The patent implements preliminary action by organizing map feature fragments into a pre-filtered hierarchical structure during data ingestion and indexing. Non-spatial attributes are processed and organized in advance within the tree structure, allowing the server to perform initial filtering operations before data transmission. This preliminary organization reduces the amount of data that needs to be transmitted and processed client-side, decreasing processing time while maintaining filtering accuracy through the preserved hierarchical relationships and attribute indexing.
Data Source
AI summary
A geospatial indexing module operating in a server device operates on an efficient index for retrieving and providing map features which represent geographic entities such as streets, roads, cities, states, buildings, bodies of water, etc. The index includes identification information for a map feature fragment, which represents at least a portion of a map feature, as well as a node in a tree data structure to which the map feature fragment corresponds and a range of levels of detail for which the map feature fragment is valid. When a user requests map data for a geographic region at a level of detail, the geospatial indexing module queries the index for all map feature fragments within the requested region and level of detail and provides the retrieved map feature fragments to the user.