Supervised Classification

In this lab, a supervised classification of current land use in Germantown, Maryland was conducted using ERDAS Imagine. AOI signatures were selected by hand using the polygon tool and recorded in the Signature Editor dialog box. All signatures were analyzed through the Mean Plot tool to determine which bands provided the greatest difference between signatures. The bands 3, 4, and 5 provided the greatest difference in signatures and was set as the band combination to reflect the data best. The signatures were then run through the Supervised Classification tool, with an additional Distance File output to show if any signature features are likely to have the wrong classification (symbolized as bright spots). The Distance File is used as a reference for correcting any wrongly classified signatures. Lastly, the supervised image is recoded by consolidating the signatures to eight classes. Those classes are agriculture, deciduous forest, fallow field, grasses, mixed forest, roads, urban/residential, and water. The final output map was created through ArcMap.