Performance of Spatial Distribution Quality by Ordinary Fuzzy Kriging for Soil Properties under Uncertainty

This research studies the spatial distribution quality of interpolation methods. The aims first to obtain unbiased estimator parameters based on regionalized variables in study field. We used kriging techniques (called Local interpolation) rely variogram function with a fuzzy inference system, where is an extension ordinary kriging. second objective this work estimate covariance models real data soil chemicals, adopted taken from (100) for each chemical (Mg, Cl, and No3). These are Mosul Quadrangle city Iraq. After applying we show minimization estimation variance choose sentimental under uncertainty. get Smallest standard cross-validation errors. Covariance described by exponential, spherical model. With best fitting constraint weights note that performance method better compared system. In conclusion, improvement does not statistical methods, but rather higher large should be improve prediction process. All programming computations carried out Matlab Language.