Improving the positional accuracy of an existing data set is a three stage process:
- Generate shift vectors
- Apply shift vectors
- Validate results
Our solutions assist customers at each stage.
Generating shift vectors
We can determine the adjustment required for every feature or vertex in order to align it with the accurate positions.
Matching data between old and new sets can be challenging, especially when, real-world changes have been applied to the newer data. Our intelligent, rules-based technology can compare data points across different data sets and infer the required shift vectors.
Applying shift vectors
Once determined, the shift vectors must be applied to all related data to make the required changes.
We take a triangulation-based approach to shifting your data, which unlike other shifting algorithms shifts data in an intelligent, context-sensitive way that ensures geometric connectivity is maintained and handles shift vectors of varying density.
Validating the results
Validation is vital. Our automated data validation ensures that relationships between features are the same before and after the exercise. Rules-based automation very quickly identifies any areas within the adjusted data that require attention.
Critically, our rules-based automated approach across every stage of the Positional Accuracy Improvement process ensures that your data downtime is minimised. The processing period during which your spatial data is unavailable is reduced and the organisational window of disruption is minimised.
For help getting your data into shape and keeping it that way, please contact us.