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Image classification is the process of categorizing each pixel in a remotely sensed image according to a land cover and land use classification system known as the schema. Geographic maps can be made using the output raster from image classification. There are two ways of categorization: supervised and unsupervised, depending on how the analyst and the machine interact during classification. They both have the option of being pixel-based or object-based.

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Supervised classification is where a person decide what class categories he want to assign pixels or segments to. These class categories are referred to as his classification schema. After the classification is complete, the person will have to go through the resulting classified dataset and reassign any erroneous classes or class polygons to the proper class based on his schema.