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Alteration of Soil Properties through a Weathering Sequence as Evaluated by Spectral Reflectance

Dep. of Soil Science, Univ. of So Paulo, Escola Superior de Agricultura "Luiz de Queiroz", P.O. Box 9, 13418-900, Piracicaba, So Paulo, Brazil

Gilberto J. Garcia

Dep. of Cartography, So Paulo State Univ., Geosciences Inst., P.O. Box 178, Rio Claro, So Paulo, Brazil

*Corresponding author (jamdemat{at}carpa.ciagri.usp.br).

ABSTRACT

In the study of physical, chemical, and mineralogical data related to the weathering of soils and the quantification of their properties, remote sensing constitutes an important technique that, in addition to conventional analyses, can contribute to soil survey. The objectives of this research were to characterize and differentiate soils developed from basaltic rocks that occur in the Paraná state, Brazil and to quantify soil properties based on their spectral reflectance. These observations were used to verify the relationship between the soils and reflectance with regard to weathering, organic matter (OM), and forms of Fe. From the least to the most weathered soil, we used a Typic Argiudoll (Reddish Brunizem), Rhodudalf (Terra Roxa Estruturada), and Rhodic Hapludox (Very Dark Red Latosol). The spectral reflectances between 400 and 2500 nm were obtained in the laboratory from soil samples collected at two depth increments, 0- to 20- and 40- to 60-cm, using an Infra Red Intelligent Spectroradiometer (IRIS). Correlation, regression, and discriminant estimates were used in analyzing the soil and spectral data. Results of this study indicated that soils could be separated at the soil-type level based on reflectance intensity in various absorption bands. Soil collected in the 40- to 60-cm depth appeared to have higher reflectance intensities than those from the 0- to 20-cm depth. Removal of OM from soil samples promoted higher reflectance intensity in the entire spectrum. Amorphous and crystalline Fe influenced reflectance differently. Weathering of basaltic soils was correlated with alterations in the reflectance intensities and absorption features of the spectral curves. Multivariate analysis demonstrated that this technique was efficient in the estimation of clay, silt, kaolinite, crystalline Fe, amorphous Fe, and Mg through the use of reflected energy of the soils.

Received for publication April 10, 1997.

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