## 6 Discussion  
The assessment of spectral unmixing results was carried out into three directions, namely, in terms of (1) the agreement of the unmixing results with the available geological information, (2) the agreement among the results obtained by the three sensors, and (3) the characteristics of the spatial distribution pattern of the hydrothermal alteration as they were mapped by the three sensors. Since the assessment was carried out quantitatively, we first computed the following three quantities. 1. Associating the \"low\", \"intermediate\", and \"high\" values of the hydroxyl-bearing alteration abundances with the \"weak alteration\", \"middle alteration\", and \"strong alteration\" categories given in the sketch map of the distribution of hydrothermal alteration in the hydrothermal field of the southern Lakki plain shown in [68], respectively, we calculated the confusion matrices and overall accuracies (one for each dataset) concerning NHASI, with respect to the reference map. In the same spirit, we associated the \"low\", \"intermediate\", and \"high\" values of the NHASI index with the \"weak alteration\", \"middle alteration\", and \"strong alteration\" categories given in the reference map and calculated the respective confusion matrices and overall accuracies. To achieve this, we digitized, georeferenced, and co-registered the sketch map. We then digitized the three different alteration categories and produced a classification map (named hereafter \"reference map\") with three classes, namely, \"weak\", \"medium\", and \"strong\" alteration, as described by [68]. We then quantized the NHASI and hydroxyl-bearing alteration abundance maps into three groups. Specifically, let \(X\) denote a map that may be either an NHASI or a hydroxyl-bearing alteration abundance map. Neglecting the pixels of \(X\) where no alteration information is given by the reference map, we divided the range of values of the remaining pixels (which correspond to some degree of alteration) of \(X\) into three intervals as follows: Denoting by \(n_{w},\ n_{m},\ n_{s}\) the number of pixels that were characterized as \"weak\", \"middle\", and \"strong\" alteration, respectively, in the reference map, the first (leftmost) interval contained the \(n_{w}\) lowest values of \(X\), the next (middle) interval contained the next \(n_{m}\) lowest values and, finally, the last (rightmost) contained the \(n_{s}\) highest values of \(X\). Actually, this can be seen as a histogram equalization process of \(X\), with respect to the reference map. The pixels of \(X\) that were in the lower-valued interval were labeled as \"low\" value pixels, those that were in the second interval were labeled as \"intermediate\" value pixels, and those that were in the third were labeled as \"high\" value pixels. Then, we calculated the confusion matrix (CF). In our case, this was a 3x3 matrix where the rows corresponded to classes \"weak\" (first row), \"middle\" (second row), and \"strong\" (third row) from the reference map and the columns corresponded to the \"low\" (first column), \"intermediate\" (second column), and \"high\" (third column), associated with \(X\). The \((i,j)\) entry of \(CF\) equaled the number of pixels that belonged simultaneously to the \(i\)-th class of the reference map and \(j\)-th interval of values in \(X\). For example, the (1,2) entry of \(CF\) contained the pixels that were characterized as \"weak\" alteration in the reference map and \"intermediate\" valued in \(X\). Based on the \(CF\), the overall accuracy was the ratio of the sum of the diagonal elements of \(CF\) divided by the total number of pixels (recall that we are referring only to the pixels that were characterized as altered to some degree in the reference map). Table 3 contains the \(CF\)s and the associated overall accuracies (OAs) for all six maps (the NHASI index map and the hydroxyl-bearing alteration SU map, for each one of the three datasets). 2.