Comparison of Spatial Interpolation Methods for Mapping the Qualitative Properties of Soil
The high proliferation rate of population and their over growing demands for foods that rely on environment and natural resources resulted in evaluation and recognition of more inputs, in particular soil and water resources. In this regard, mapping the soil properties is considered as well-adopted approach to provide fundamental information related to land resources. As a branch of applied statistics, geostatistics uses the collected information sampled location to provide a broad range of estimates concerning the land properties in unsampled locations. In the present study, we evaluated the performance of estimates kriging, inverse distance weighting, and Cokriging to map some of the soil quality properties in chat fields of Golestan province located in northern part of Iran. We measured percentage of clay, silt, sand, calcium carbonate, organic carbon, and concentrations of micronutrients such as iron, copper, zinc, manganese, and concentrations of macronutrients including nitrogen, potassium, and phosphorus as main parameters affecting the soil quality. Sampling was performed on grids 250 × 250 meters in 35 points of the depth of 20 cm. After data normalization, experimental semivariograms was drawn. For Kriging and Cokriging estimation we utilized spherical, exponential, circular, and Gaussian models, and to estimate variables using Inverse Distance Weighting, the parameters of 1-5 power was used. Kriging method was found to the two other methods for estimation of soil properties under study. For the estimation of electrical conductivity and soil’ iron content, the Kriging and Cokriging showed the best estimation of results. However, to estimate the other parameters of soil (sand, organic carbon, pH and lime) inverse distance weighting method with power one was found to have the least error leading to the best interpolation. Finally, considering the best method of interpolation, zoning maps of soil quality properties was created in the GIS.