Universal Kriging Prediction of nonstationary Spatial Stochastic Process

Spatial Stochastic processes are often divided into two types that are stationary spatial stochastic processes and other nonstationary.In most practical applications the processes are nonstationary .Prediction of these processes are performed by universal Kriging technique which supposes that the processes have a trend with fixed linear or nonlinear equation.In this work we derive the universal Kriging equations in matrixes form which can easily be implemented by computer. Also here we identify the variogram model and trend model.The application is given in example that worked out on real data. The predicted results are very near to the real data with error of prediction is given