This points to what was written above concerning reading off information form the feature space, in particular being able to understand the meaning of colour coded clusters and being able to relate them to the image from which they are derived. Associating individual clusters with individual features in the image - This refers to the process of labeling clusters in the feature space according to what areas or segments of the image space they represent. The first is with a pair of Physics four students. The second group are a collection of six M.Sc. They primarily use Landbase images and never use met images.
Landbase images are somewhat easier to interpret since the features are typically more distinctive.
Their task could be described more like map reading and interpretation. In contrast to the Physics 4 students, the M.Sc's perform principal component analysis on the data. This allows them to analyse the data into its principal components and to take note of the important features in the transformed data. The typical approach to the task consists of viewing the image with two of three channels. The channels Red Green and Blue refer to the visible and infra red spectra.