comparison of geostatistical methods for prediction of soil parameter in plant community of nitraria schoberi(arid regions)

geostatistical approaches have great importance because they include spatial correlation of geographic data. present study evaluated the efficiency of geostatistical techniques and demonstrated their capabilities in studying the soil variables(soil texture (sand percent), ec and so4-2) in the important plant community of nitraria schoberi in meighan desert, arak. a regular grid on the map comprising rectangular cells was designed and situated over the experimental area with 98 points for vegetation type. the grid was laid out in the field using the global positioning system. soil samples were taken between 0-20 and 20-100 cm layers for each point. analysis using the best view at semivariogram model were applied to select the gaussian models of soil characteristics with r2 higher than 0.95. among ordinary kriging, simple kriging and inverse distance weighting methods, ordinary kriging method showed the best cross-validation criteria (mean square error and average error) and had higher prediction accuracy than others. finally, spatial estimates of the soil characteristics were performed using ordinary kriging.