Spatial Prediction of Real Sulfur Data Using the Ordinary Kriging Technique and Lognormal Kriging

Abstract

This research deals with the spatial prediction process in order to obtain the optimal prediction when the data are distributed normally. In this paper, we used the ordinary kriging technique and the lognormal kriging after taking the logarithm of the original sulfur data. We used the variogram function in this research to get the best model for the covariance function. The aim of this research is to evaluate the normal kriging and the lognormal kriging and find outliers. The data adopted in this work are from the hydrogeological study of Mosul Governorate/Iraq. Through the results, it was found that the errors in the estimated value are very important for the variance of the estimator, which appears to be very small. As well as through the results that were supported by graphs, we note that the lognormal kriging has more effect than the ordinary Kriging technique under the prediction process, from During the implementation of the error tests which seemed to be very small and which support the predictive values ​​of the spatial sulfur data, the MATLAB programming language was used to obtain the practical results.