Unsupervised & Supervised Classification

 This week we return to using ERDAS imagine in order to look into different ways of classifying satellite imagery.  The process of classifying imagery is where all the values of a raster image are assigned to a value, such as a land cover or use type.  This can be done by hand (unsupervised) or automatically (supervised) based off of areas of interest (AOI).  Once areas of an image are classified, it is possible to preform calculations such as the amount of area a particular classification takes up.

This depicts how land is used within Germantown, Maryland.  Tracking land use over time is a good way to measure how different areas have urbanized.