Unsupervised & Supervised Classification Lab 5

This week's lab focused on unsupervised vs. supervised image classification. Image classification is the process of giving pixels in an image unique values. Unsupervised classifies without predefined training data, while supervised classifies guided by known training samples. The map below shows a supervised classification of the city of Germantown, Maryland. It was created by using the inquire(legacy), the growing properties, and signature editor features in ERDAS Imagine with the given coordinates. The map shows different types of land use and their coverage. The unique classes chosen were Urban, Road, Deciduous Forest, Mixed Forest, Fallow, Agriculture, and Water. The area of each is shown in the legend in acres. A inset map of the distance image map is also included.