Impacts of Class Spectral Variability on Soft Classification Prediction and Implications for Change Detection

Soft classification accuracy was negatively related to the degree of intra-class variation. Moreover, the utility of a single value prediction of the fractional cover of a class derived from a soft classification declined as level of intra-class variation increased and it may be preferable instead to derive a distribution of possible fractional covers. The distributional output may also help in the evaluation of change derived from the use of a post-classification comparison analysis.