GeoBayesian Modeling

The Geobayesian model in SADA integrates bayesian update methods with standard geostatistical approaches in an effort to better characterize site conditions and to reduce the number of samples required. Bayesian methods are often used in statistics to make use of information available from prior knowledge, while geostatistics can be used to make more efficient use of spatial data. This approach first presented by Johnson (1996) incorporates prior knowledge or "soft information" explicitly in the process, integrating it with hard sample data to produce a combined or collective characterization result. "Soft information" is data other than the results of specific measurements.

The following interviews are available for Geobayesian data in SADA:

   View My Initial Probability Map

   View My Initial Variance Map

   Draw an Area of Concern Map Based on Soft Data Only

   Calculate Cost versus Cleanup Based on Soft Data Only

   Develop a Sample Design

More interviews become available after importing sampled data:

   Update My Prior Probability Map

   Update My Prior Variance Map

   Draw an Area of Concern Map

   Calculate Cost versus Cleanup