What is supervised classification? Describe the various steps involved in supervised classification.

Supervised classification is a method used in remote sensing and image analysis to categorize pixels or objects within an image into predefined classes or categories based on training data with known class labels. It involves training a classification algorithm using a set of representative samples from the image, where each sample is associated with a known class label. The trained algorithm is then applied to classify the remaining pixels or objects in the image based on their spectral or spatial characteristics. Here's a detailed description of the various steps involved in supervised classification:

1. Selection of Training Data:

• The first step in supervised classification is the selection of training data, which consists of representative samples from each class or category present in the image.
• Training samples should be selected to capture the variability and spectral __________ ______ _______ ___ ______ _________ _______ ____ __________ _________ ___ ____.
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