Diffuse reflectance spectroscopy (DRS) can be used as an alternative in identifying and quantifying some soil properties such as particle size and soil organic matter (SOM). This technique may be an alternative to quantifying those properties in a large volume of soil samples since it is faster and less costly and does not produce chemical residues. The aim of this study was to develop models using multiple linear regression analysis to predict the content of clay, sand, silt, and SOM using DRS data in an area of complex topography and geology located in the central region of Rio Grande do Sul, Brazil. In the study, 303 samples were collected at a depth of 0.00-0.20 m for determination of clay, sand, silt, and SOM by laboratory and spectral reflectance analysis. The predictive models produced high-quality results, explaining 77 and 72 % of the variance for sand and clay, respectively. The interpolation maps of the observed and predicted properties revealed that the spatial patterns are mainly associated with the topography and geology of the area. Even with the geological and pedological complexity, the results indicated that the technique is promising and it may be applied for prediction of particle size and SOM.
pedometrics; proximal remote sensing; radiometry; attributes predictions
