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Supervised classification is a widely used image classification technique in remote sensing and digital image processing. It involves the use of known data, called training samples, to classify unknown pixels in satellite or aerial imagery. The technique requires prior knowledge about the land cover types present in the study area. This knowledge is used to train the classification algorithm, which then categorizes all image pixels into the predefined classes. Supervised classification is a pixel-based approach and is preferred when ground truth information is available for the region of interest. The process of supervised classification consists of several essential steps: 1. Selection of Training Sites: This is the first and most critical step. The analyst selects representative areas for each _____ _____ ______ _____ ___ __________.
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