Positional Accuracy Improvement (PAI)

FREE Positional Accuracy Improvement White Paper

There’s just never a “right time” to run a Positional Accuracy Improvement (PAI) project, but there is a “right way” – one that minimises risk, disruption and cost. Download our FREE PAI White Paper to find out more.

Improve the absolute accuracy of your positional data

Positional accuracy describes the difference in position between representations of a single point on two different geospatial layers, or between a single layer and reality.

Inaccuracy is often a problem for organisations that have data sets pre-dating the use of accurate GPS surveying technology. In many such cases, the position of any point within the data set is accurate relative to other points in the same set, but can be very inaccurate relative to more recent, more precise data.

This is a problem both for suppliers of base data who need to update its positional accuracy and also for users of this data whose assets will need to be shifted to stay in sync with the updated base data.

Positional accuracy is often a variable problem. Typically, data relating to urban areas is relatively accurate while rural data can suffer from wide variations.

“To re-align our network on a more precise Cadastre base-map, we called upon 1Spatial services team to implement their 1Integrate solution. The results obtained were exactly what we required. Furthermore this Positional Accuracy Improvement (PAI) solution does not halt or affect data production therefore representing great operational advantages.”

Christophe ARTAUX, GIS & Mapping Department Manager, Rhône-Alpes-Auvergne | Suez Eau France

Improving the positional accuracy of an existing data set is a three stage process:

  1. Generate shift vectors
  2. Apply shift vectors
  3. 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.

Contact us

For help getting your data into shape and keeping it that way, please contact us.

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