Supervised Classification: Germantown, MD

What a week it has been. In Photo Interpretation, we continued learning about classification of aerial images. This week was Supervised Classification. Using ERDAS Imagine, and a raster image of Germantown, MD, I created my own Spectral Signature and Supervised Classification. I used the AOI Seed tool (Drawing tab, Insert Geometry group, press the Grow dropdown arrow, then click Growing Properties) to designate eight areas (pixels) on the image that were of a particular type of land cover, including:

Urban/residential  

Grasses 

Deciduous Forest

Mixed Forest (Deciduous/Conifer)  

Fallow Field

Agriculture

Roads

Water

I used Mean Plots and Histograms to evaluate where there was Spectral Confusion. More accurately, I was looking for areas where the Mean Plot lines did not converge or which bands had the most separation. I discovered that my Plots had the most spectral separation in Bands 1 -2- and 3. Then I used the  Maximum Likelihood tool to classify my image after setting color to "Approximate true color."   

The result of my work including a Distance Map is shown below.