Digital Elevation Model Quality Control via Slope-Adaptive Validation
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Solution Overview
Problem
Current methods for ensuring the accuracy of digital elevation models (DEMs) are labor-intensive and prone to human error, requiring tedious manual review and consuming valuable resources.
Innovation Solution
An automated system and method for updating DEMs by comparing two DEMs of the same geographic area, identifying deviations in z-values, and adjusting them based on terrain slope-defined tolerance rules to ensure consistency and accuracy without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review processes are used to ensure DEM accuracy, then quality control can be performed, but labor time and resource consumption increase significantly
Solution Approach 1:
The system performs self-validation by automatically comparing new DEM data against existing DEM data and quality rules, eliminating the need for external human reviewers. The automated quality control system serves itself by detecting and flagging inconsistencies without human intervention
Solution Approach 2:
The patent replaces the mechanical human review process with an automated computational system that uses algorithms to compare DEM datasets, evaluate quality rules, and identify inconsistencies. This substitution eliminates manual labor while maintaining quality control effectiveness
2Reliability
If manual review processes are used to ensure DEM accuracy, then quality control can be performed, but resource consumption increases
Solution Approach 1:
The automated system performs self-validation by automatically comparing new DEM data against existing DEM data and quality rules, eliminating the need for external human reviewers. The automated quality control system serves itself by detecting and flagging inconsistencies without human intervention
Solution Approach 2:
The patent replaces the mechanical human review process with an automated computational system that uses algorithms to compare DEM datasets, evaluate quality rules, and identify inconsistencies. This substitution eliminates manual labor while maintaining quality control effectiveness
3Productivity
If automated processing is implemented, then productivity increases, but measurement precision may be compromised
Solution Approach 1:
The system implements feedback mechanisms by automatically comparing processed DEM data against established quality rules and existing DEM datasets. The system evaluates discrepancies, flags inconsistencies, and provides feedback on data quality, ensuring automated processing maintains measurement precision through continuous validation
Solution Approach 2:
The patent applies preliminary quality rules and validation criteria before final DEM processing completes. By pre-defining acceptable elevation changes, slope constraints, and data consistency requirements, the system ensures measurement precision is maintained throughout the automated processing workflow
Data Source
AI summary
A method can include receiving, first and second digital elevation models (DEMs) including first elevation data of a geographic location and second elevation data of the geographic location, respectively, identifying differences between the first elevation data and the second elevation data that are greater than a first threshold, determining, for a point in the second elevation data identified to correspond to a difference greater than the first threshold, a slope of the geographic location around and including the point, and altering, in response to determining the difference is greater than a second threshold determined based on the determined slope, elevation data of the second DEM corresponding to the point.