Knowledge of the variability and spatial structure of soil properties is essential to determine the optimal support for collecting soil samples and also for effectively applying management decisions in the field. The degree of spatial dependence of different soil properties is often determined by using the nugget to sill ratio (NR). The NR is widely used and provides good information on the spatial dependence but ignores information about spatial structure that is contained in the range and the semivariogram model form. Therefore, the objective of this study was to discuss NR and other alternative approaches to exploring, characterizing, and comparing spatial dependence of isotropic second order stationary spatial processes. Soil samples were collected at the center of a regular grid of 50 m × 50 m and also on the grid line during Nov. 2008 and 2009 from 0-15 cm depth. Geostatistical software (GS+, Gamma Design Software, Plainwell, MI) was used to estimate the variance structure of sand, clay, soil bulk density (ρ_b), saturated hydraulic conductivity (Ks), pH, electrical conductivity (EC), nitrate-nitrogen (NO₃- N), chloride (Cl), and volumetric water content (θ) at six different matric potentials (Ψ_m) (–33, –100, –300, –500, –1000 and –1500 kPa). The alternative approaches included in this review were scaled semivariogram, correlogram, and integral scales. Both correlogram that is negatively related to the scaled semivariogram and integral scale that incorporate spatial information contained in the range can provide single number spatial dependence summaries.