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ABSTRACT Various attributes are often required to build soil quality indicators. However, determining these attributes is time-consuming and requires several specific devices. Thus, it is desirable to develop indexes that express soil quality based on easily determined attributes. The objective of this study was to investigate the spatial variability of the S index and its correlation with other physical and chemical soil attributes to generate a pedotransfer function for estimating the S index. A georeferenced sampling mesh covering 1.4 ha and employing 71 points was installed. The soil samples were collected in 0.00–0.15 m and 0.15–0.30 m deep layers to determine the physical and chemical attributes. The results indicated that the S index was correlated with porosity, carbon stocks, cation exchange capacity, and particle size fractions. However, macroporosity, microporosity, and sand content were the most suitable attributes for the construction of pedotransfer functions. A principal component analysis indicated that the S index was representative of 9.4% and 11.5% of the total variability in the dataset in the respective soil layers. Spherical semivariogram models showed that the S index was spatially dependent and ranged between 84–188 m. The S index maps estimated by the pedotransfer function resemble the observed S values; therefore, the function can be applied in spatial variability studies.