Reflectance Spectroscopy as a Tool for Monitoring Contaminated Soils

Visible, Near-Infrared, and Mid-Infrared Spectroscopy Applications for Soil Assessment with Emphasis on Soil Organic Matter Content and Quality: State-of-the-Art and Key Issues

“…The independent data matrix (spectral data) is transformed by PCA, and the first few principal components (PCs), which show most of the independent data variance, are used as inputs for the MLR model instead of the original spectral data. 59 Schwartz et al 59 stated that the advantages of this method over SMLR are that the PCs are uncorrelated and the noise is filtered. The first few PCs are usually enough for a robust model, and over-fitting issues can be removed.…”

“…Learn-ing is a repeating process in which the resulting output is compared to the given expected output and the algorithm adjusts the weights accordingly. 59 In a recent large-scale study that included over 1100 soil samples, ANN was proven to provide better results than PLSR in modeling soil constituents. 29 Although this method is often used to deal with nonlinear models, it is not popular with researchers due to some problems, such as the selection of hidden layer size, learning rate, and momentum.…”

“…The regression coefficients are estimated by reducing the error between predicted and observed response values in a least squares sense. 59 The SMLR approach often causes severe problems because of multicollinearity among the reflectance measurements of the selected wavelengths. In particular, the estimated regression coefficients vary markedly when the outlying observations are changed or deleted.…”

“…According to Schwartz et al, 59 a global soil spectral library, not only for minerals but also for chemical information, has to be maintained because all these factors can influence soil reflectance spectra. In the laboratory, using different spectrometers, or even repeating measurements of a specific sample using the same spectrometer, may result in variations in spectra.…”

“…Each spectrum is then corrected such that all samples appear to have the same scatter level as the reference spectrum. 58,59 In SNV, the slope variation from spectra caused by scatter and variation of particle size is removed.…”