Variations in reflectance of tropical soils: Spectral-chemical compositionrelationships from AVIRIS data

The relationships between Airborne Visible. Infrared Imaging Spectrometer ( AVIRIS) surface reflectance values and constituents (total iron, organic ma tter, TiO2, Al2O3, and SiO2) of samples representative of three important s oil types from central Brazil [Terra Roxa Estruturada (S-TE), Latossolo Ver melho-Escuro (S-LE), and Areia Quartzosa (S-AQ)] were analyzed. End member spectra for green vegetation (GVd), nonphotosynthetic vegetation (NPV), wat er (W), and the three soil types were selected by inspecting scatter plots derived from the principal components analysis (PCA) of 140 AVIRIS bands. T hey were then used to compose a six end member unmixing model to characteri ze the spectral reflectance variations associated with the different scene components, the spatial distribution of the soil types, and the effects of spectral mixing on the spectral-chemical composition relationships. Finally , regression equations fitted to soil constituents and their highly correla ted spectral bands were used to produce maps showing the chemical variabili ty in the scene for areas dominated by the presence of exposed soils, as in dicated by the results from the unmixing model. The results showed a very g ood agreement between the spatial variability of the soil types and of the soil constituents. The largest squared correlation results were obtained fo r Fe2O3, TiO2, and Al2O3, but the relationships were affected in the transi tion from the red to the near-infrared interval by the presence of nonsoil residues (e.g., senescent vegetation or litter) over the soil surfaces. In comparison with the light and loamy sand S-AQ, the dark-red clay S-TE and S -LE presented higher contents of Fe2O3, Al2O3, and TiO2, and consequently l ower overall reflectance in the scene, because of the presence of greater a mounts of opaque minerals. The prediction of these constituents from remote sensing data and their close association with the spatial distribution of the different soil types demonstrate the importance of the present investig ation for soil mapping and soil erosion studies. (C) Elsevier Science Inc., 2001. All Rights Reserved.