This video shows you how to conduct a supervised classification after the image has been preprocessed and the training areas have been collected.
After classifying the image, it is often necessary to recode categories, edit some obvious errors in the result or eliminate isolated pixels. Those post-processing steps are shown in the second part of this video.
Moving forward in this mini-series on image processing with the Semi-automatic Classification (SCP) plugin in QGIS, we will see how to carry out the creation of training areas required for supervised image classification.
In addition we will see how to create and edit the spectral signatures and how to preview the result of the classification based on the algorithm and the signatures collected.