For vegetation species discrimination involving bulloak tree spectra against the other woodland vegetation species, the prediction accuracy of raw spectra is reasonably higher than the accuracy of transformed spectra (smoothing and MSC) as depicted in Tables 4 and 5 for both canopy and leaf levels. Overall, the prediction accuracies of raw spectra and smoothing were nearly the same, whereas MSC’s prediction accuracies consistently produced the lowest accuracies. For example, prediction accuracies of raw spectra and the smoothing method for bulloak versus apple gum, as well as for bulloak versus cypress (canopy level), were nearly the same. They were 92.67% (raw) and 92.64% (smoothing) for bulloak versus apple gum, while they were 95.67% (raw) and 95.67% (smoothing) for bulloak versus cypress. At the leaf level, similar patterns were observed: for bulloak versus dogwood, the accuracies were 92.45%, 92.54%, and 81.82% for raw spectra, smoothing, and MSC, respectively. This situation indicated that the raw and smoothing spectra have equivalent predictive power for species discrimination when evaluated by PLS regression.