Bayesian Melding of Deterministic Models and Kriging for Analysis of Spatially Dependent Data

The link between geographic information systems and decision making approach own the invention and development of spatial data melding method. These methods combine different data sets, to achieve better results. In this paper, the Bayesian melding method for combining the measurements and outputs of deterministic models and kriging are considered. Then the ozone data in Tehran city are analyzed by using these methods. Next their results are evaluated and compared in terms of mean square error criterion. Finally, discussion and results are given.