Geostatistics provides suitable methods that allow you to integrate all acquired data to predict activity concentration levels at unsampled locations. In addition to such contamination mapping, quantifying the uncertainty related to the estimates will help you anticipate potential risks or discoveries that may occur during remediation.

Deliver robust radiation maps
Kriging is a well-known and robust technique used in geostatistics to interpolate and predict values from a set of measurements combined with the variogram model. The main result is the generation of 2D and 3D contamination maps. The kriged map is associated with a variance map, which quantifies the uncertainty related to the estimation. It depends on the distance of an interpolated point from the observation point, sampled or measured, and the spatial structure thanks to the variogram model.
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– Watch our video about the mapping of Fukushima contaminated area with Kartotrak”→

Benefit from all available information
When different types of measurements or various contaminants are available, multivariate geostatistics (or cokriging algorithms) may be used to reduce estimation uncertainty and improve map quality. The technique takes advantage of the correlation between contamination and environment variables (e.g., between activity levels and a Digital Elevation Model, for example). It beneficially integrates auxiliary data, which is more abundant in space, like dose rates (or any in situ measurement), in comparison to lab analyses on destructive samples, to produce maps with more spatial details. Multivariate analysis is also interesting from a financial viewpoint since the auxiliary datasets are less expensive and quicker to collect, or even sometimes already existing in the archives/records.

Inform your decisions with comprehensive uncertainty analysis
More advanced and sophisticated geostatistical methods, such as conditional expectation or geostatistical simulations, can be used to quantify different uncertainties – the risk of exceeding a threshold, for instance. These estimates are powerful decision-making aids when classifying surfaces and volumes before decontamination begins (based on different radioactivity thresholds and risk levels and considering the remediation support impact).
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– Download our article about radiological characterization for decommissioning a nuclear facility to find out more →