Absolute Geospatial Accuracy Estimation Without Ground Control Points
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Determining absolute geospatial accuracy in satellite or aerial imagery without surveyed control points is challenging due to the expense and unavailability of ground control points (GCPs) in many regions.
Innovation Solution
The method estimates absolute geospatial accuracy by calculating a statistical measure of relative accuracies between pairs of overlapping images, using a root mean square error of the shears between these images, without relying on surveyed geospatial reference points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surveyed control points (GCPs) are used to determine absolute geospatial accuracy, then measurement precision is improved, but cost and availability deteriorate
Solution Approach 1:
The patent introduces relative accuracy measurements between overlapping images as an intermediary method. Instead of directly measuring absolute accuracy against GCPs, the system uses tie points between image pairs to compute relative accuracies, which then serve as a basis for estimating absolute accuracy through statistical aggregation. This intermediary approach eliminates the need for physical GCPs while maintaining measurement capability.
Solution Approach 2:
The patent creates a virtual reference system by using tie points from overlapping images as substitutes for physical GCPs. The relative accuracy measurements between image pairs are copied and aggregated to form an estimate of absolute accuracy, effectively creating a computational substitute for traditional surveyed control points.
2Measurement precision
If surveyed control points are obtained through manual GPS measurement, then absolute geospatial accuracy is improved, but time consumption and labor cost increase
Solution Approach 1:
The system performs self-service by using the image data itself to determine accuracy. Overlapping images automatically provide tie points through correlation algorithms, and the system computes relative accuracies without external intervention. This self-service mechanism eliminates the need for time-consuming manual GPS surveying and field measurements.
Solution Approach 2:
The patent performs preliminary actions by computing relative accuracies between all overlapping image pairs before aggregating them into an absolute accuracy estimate. This preliminary computation of relative measurements between images prepares the data structure needed for final accuracy determination, eliminating the need for sequential field surveys.
3Measurement precision
If traditional GCP-based methods are used, then absolute geospatial accuracy measurement is possible, but adaptability to restricted regions deteriorates
Solution Approach 1:
The patent creates a universal method that functions across diverse regions without requiring local GCPs. The relative accuracy measurement approach using overlapping images works equally well in politically restricted areas, geographically difficult regions, and standard environments, making the system universally applicable regardless of location-specific constraints.
Solution Approach 2:
The patent extracts the accuracy measurement capability from the physical GCP framework and relocates it to the image correlation domain. By removing the dependency on physical control points and using only image data and satellite metadata, the system becomes adaptable to any region where satellite imagery can be obtained, including restricted areas.
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
Estimating absolute geospatial accuracy in input images without the use of surveyed control points is disclosed. For example, the absolute geospatial accuracy of a satellite images may be estimated without the use of control points (GCPs). The absolute geospatial accuracy of the input images may be estimated based on a statistical measure of relative accuracies between pairs of overlapping images. The estimation of the absolute geospatial accuracy may include determining a root mean square error of the relative accuracies between pairs of overlapping images. For example, the absolute geospatial accuracy of the input images may be estimated by determining a root mean square error of the shears of respective pairs of overlapping images. The estimated absolute geospatial accuracy may be used to curate GCPs, evaluate a digital elevation map, generate a heatmap, or determine whether the adjust the images until a target absolute geospatial accuracy is met.