GIS 4035 - Module 9 - Unsupervised Classification

This week we were tasked with performing an unsupervised classification of our very own UWF campus here in Pensacola, Florida. The unsupervised classification was ran using ERDAS.
UWFclass50.img was created with the following settings : classes 50, RGB 321, maximum iterations 25,
convergence threshold 0.950, skip factors x: 2 y: 2.  Attribute table data was opened and the following category names were applied to the following pixel features in the UWFclass50.img:
Trees – dark green, Grass – green or chartreuse, Buildings/Road – grey,
Shadows – black, Mixed – light green
All 50 classes were recolored and renamed T, G, B, S, or M
Area was manually calculated and determined to be .90 square miles. Impervious percentage
calculated as 25% and Pervious percentage calculated as 75%.