The use of remote sensing techniques in soils studies is relatively new. Further research in this area should be made. The objective of this work was to estimate chemical and granulometric attributes of soil from Ibaté and São Carlos counties, State of São Paulo, through multiple and linear regression equations generated with reflected electromagnetic information collect by sensors installed in laboratory and satellite. An analysis of the economic viability of the sensor uses for quantifying soil attributes were carried out in comparison with the conventional method of soil analysis. It was collected and georeferenced 319 soil samples. The soil samples were evaluated by laboratory sensor (FielSpec) and orbital image (ASTER). Spectral prediction models were elaborated for both acquisition levels. The models were used to determine the attributes on unknown samples. It was possible to quantify some soil attributes, such as clay (R² = 0.69) and sand (R² = 0.53) content using the reflected electromagnetic energy measures by terrestrial sensor. The orbital sensor showed good results to predict coarse sand (R² = 0.45) e total sand (R² = 0.41). It was verified that the attribute analysis by sensors can be cheaper and faster to assist the traditional method of soil analysis.
sensors; properties' quantification; precision agriculture
