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