Detailed soil information and soil maps are essential for the monitoring, management, conservation and restoration of natural ecosystems, rangelands and protected areas. Semi-automated mapping methods have advantages over conventional ones, and the selection of the best interpolation method and accurately predicted soil property maps are important for effective management and conservation strategies. Spatial soil information is important also for managing natural resources, predicting soil properties, improving sampling designs in future agro-ecological studies, and for assessing protected areas. We investigated the suitability of different interpolation methods for spatial variability predictions and for studying various soil properties within a rangeland ecosystem and the Sabalan National Natural Monument protected area, in northwestern Iran. Soil samples were collected randomly from a depth of 0–30 cm, and various properties were measured in the laboratory. Normality of data was examined and spatial statistics was applied to determine spatial variation of the properties. Interpolation methods of inverse distance weighting, Kriging and Cokriging were applied and compared for suitability. Results were evaluated using crossvalidation. The results of applying spatial statistics demonstrated that soil properties had spatial dependence; Cokriging emerged as the most accurate technique overall.