Multivariate analysis of laboratory spectra for the assessment of soil development and soil degradation in the southern Apennines (Italy)

Multivariate statistical analysis was applied to high resolution laboratory reflectance spectra of soil samples reflecting the range of soil development levels in a test site in the southern Apennines (Fortore beneventano) in Italy. Principal component analysis was used to identify the dominant characteristics of soil spectra and cluster analysis to group samples into homogeneous classes. The analysis was applied stepwise (1) to a minimum number of reflectance values, representative of the general shape and curvature of soil spectra, and (2) to the normalized amplitude (depth) of characteristic absorption bands. In the first step analysis, it was found that the brightness and the visible near-infrared (VIS-NIR) slope of the spectra are important spectral characteristics to discriminate soil development, also in relation to the underlying lithology. The principal intercorrelation between the brightness, the VIS-NIR spectral slope, and various soil properties, such as calcium carbonate content, organic matter, and texture, could be also explained. In the second step, it was demonstrated that different types of soil include in the homogeneous groups, resulting from the first step multivariate analysis, could be further separated, mainly as function of the iron oxide features and the two main water and hydroxyl absorption bands at 1400 nm and 1900 nm. These results suggest that our method is suitable for the evaluation and interpretation of remote sensing data for discriminating different soil development and degradation levels of large parts of the Apennines, which are similar to the test area. The brightness and the VIS-NIR slope components derived int he first step multivariate analysis may be retrievable from common multispectral systems such as Landsat-TM. The application of the second step multivariate analysis, however, would require the use of hyperspectral systems capable of retrieving the absorption features. In both cases rigorous atmospheric correction including the removal of the effects of relief illumination is a prerequisite. (C) Elsevier Science Inc., 2000.