A supervised classification of remote sensing images is a processing technique that allows for the identification of materials in the image, according to their spectral signatures (see here for further definitions about remote sensing).
The main advantage of this approach is that an entire image can be processed rapidly, producing the land cover classification thereof.
This post is about the interpretation of remote sensing images that is a fundamental phase of the ROI creation, which is a required step for the semi-automatic classification.