In module 10 we were tasked with adding unique values to all pixels in a raster image. Supervised classification involves collected sets of pixels to define spectral signatures. I then had to evaluate the accuracy and use them to classify the entire image. Once I got the signatures recoded into eight specific classes I was able to notice some spectral confusion with in the roads signature. The area was far too large for what was actually in the given image.
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