Reverse Geocoding Using Combined Point and Street Segment Datasets
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Solution Overview
Problem
Current reverse geocoding systems face limitations in accuracy due to their reliance on either point level or street segment datasets, with point datasets being incomplete in geographic coverage and lacking intersection points, while street segment datasets require interpolation for address matching, leading to fewer high accuracy matches.
Innovation Solution
A system that combines point level and street segment datasets to determine the most accurate address by analyzing geometric relationships, prioritizing point level data matches over interpolated street segment locations, and employing spatial relationships to increase overall accuracy in reverse geocoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If point level datasets are used for reverse geocoding, then address matching accuracy is improved, but geographic coverage is reduced and intersection points are lost
Solution Approach 1:
The patent combines point level datasets with street segment centerline datasets into a unified reverse geocoding system. The system first searches for matching points in the point level dataset, and when no match is found, falls back to interpolation methods using street segment centerlines. This merging approach maintains high accuracy for locations with point data while extending coverage to areas represented only by street segments, including intersection points.
2Adaptability or versatility
If street segment centerline datasets are used for reverse geocoding, then geographic coverage is improved, but address matching accuracy is reduced due to interpolation requirements
Solution Approach 1:
The patent segments the reverse geocoding process into two distinct phases: first attempting matching against point level data for high accuracy, and only when necessary proceeding to street segment interpolation for extended coverage. This segmentation allows the system to optimize for accuracy when point data is available while maintaining functionality and broader coverage when it is not.
3Measurement precision
If point level datasets are used, then address matching precision is improved, but data storage requirements and search complexity increase
Solution Approach 1:
The patent implements a hierarchical search strategy that performs a partial search in the point level dataset first, and only proceeds to the more computationally intensive street segment interpolation when the point search yields no results. This approach balances the benefits of high precision point matching with the practical constraints of data storage and processing complexity.
Data Source
AI summary
A reverse geocoding system and method processes a point level dataset and a street segment dataset to determine an address for a particular latitude and longitude of an input point entered into the system. A determination is made if the point level dataset contains a point level data address match to the entered latitude and longitude data within the closest street segment and without crossing the street segment. Any such point level data address match is output. When no such point level data address match is made, the system computes an interpolated address from a range of addresses of the closest street segment in the street segment dataset based on the entered latitude and longitude of the input point in relation to said range of addresses for the closest street segment. The interpolated address from the closest street segment in the street segment dataset is output.