Mod 5: Supervised Classification Exercise

This week we learned about Unsupervised and Supervised Classifications. The map above is a Supervised Classification where we were given an image from Germantown, Maryland and tasked with dividing it amongst 8 classes (Agriculture, Deciduous Forest, Road, Urban, Mixed Forest, Grass, Fallow, and Water) to make a land use map for their future planning. Using ERDAS Imagine I was able to create polygons for some signatures or utilize the AOI Seed tool to grow my own. By collecting the signatures, evauluating them, classifying the image, merging the classes and calculating area the process read from lecture has come to reality. Taking into consideration Spectral Euclidian Distances and Neighborhood, then checking the histograms and signature editor columns for clarification I think the output map was an overall success in this lab. The concepts involving the histogram plots, layers and bands are still a little fuzzy in my head, but exercises like this are very helpful in making things clearer.