Methods of Spatial Interpolation in The Representation of Soil Properties/Nineveh Governorate Soil Case Study

Abstract

Spatial interpolation is a process used to guess cell values at points or locations where real models are not available. The principle of interpolation is based on Spatial autocorrelation and Spatial Dependence, which measures the degree of relationship or dependence between points or objects near and far and by using statistical techniques to address the effects of data values and the relationship between the various interrelated. The study relied on more than one method of spatial interpolation (Kriging - Inverse Distance Weighted-Radial Basis Functions-Global Polynomial-Local Polynomial). To represent data for one of the most important elements of the natural environment and the soil and within the spatial space of the governorate of Nineveh, In the present study, some of the physical properties of the soil are expressed (soil texture, pH, bulk density, and chemical components such as (organic matter, total Bases, cation exchange capacity, exchangeable sodium percentage, calcium carbonate, available water capacity, and electrical conductivity based on (92) points distributed according to the results of the spatial interpolation test based on the mean bias error values and root mean square error, which was used as a criterion for the differentiation between the methods of completion used in the study. The study also showed that the Kriging method is suitable for the parts of spatial completion of soil properties. It was possible to reach (27) maps to represent some of the physical and chemical properties of the soil of the study area.