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REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEM FOR SOIL CHARACTERIZATION AND QUANTIFICATION OF IT ATTRIBUTES With the increasing in adoption of precision agriculture, there is a need more detailed information about soil spatial variability in order to make possible a better management of crop fields. However, the cost of soil chemical analysis is the most important obstacle to obtain this information. The use of geoprocessing techniques, such as remote sensing, GPS and geographic information system, for soil characterization and quantification of their attributes is a challenge pursued for several researchers because it is an alternative technology for soil evaluation that can be cheaper, faster, and with lower environmental impact. Nevertheless, like any new technology, it must be tested and adjusted with different soil types located in different areas. For this research, two areas were chosen: São Carlos and Ibaté, São Paulo region, with the following objectives: (i) characterize the soil spectral response using terrestrial (FieldSpec) and orbital (ASTER) sensors; (ii) determine the changes on soil spectral response across different toposequences; (iii) generated models to quantify soil chemical and granulometric attributes based on its electromagnetic radiation and (iv) characterize the soil in conformity with altitude and slope using geographic information system techniques. Soil samples were collected and a soil map was developed. Soil samples were analyzed by both sensors and their attributes was correlated with spectral reflectance. Then spectral models were developed to quantify soil attributes. Soil map was crossed with declivity and elevation information for characterization. It was verified that the granulometric and organic matter attributes have a great influence on soil spectral response. It was verified that soils located in higher altitudes presented higher reflectance intensity than those located in lower positions due to the variation on parent material. The correlations between soil attributes and spectral data showed a tendency to increase the correlation coefficient at higher wavelengths. The models elaborated to quantify the granulometric attributes resulted in estimated values very close to the determined by conventional laboratory analysis (clay content: R2 = 0.69). In regional scale there is a tendency of some soil classes occur at similar altitudes and slope. For example, the Typic Haplustox was found predominant at higher altitudes (815-835 m) and plan relief (1-3%). It was possible to conclude that based on information about slope and altitudes for this area, the pedologic extrapolation in new areas without field work should be done with caution.

Sensoriamento remoto e sistema de informações geográficas na caracterização de solos e quantificação de seus atributos