Photo Interpretation and Remote Sensing - Supervised and Unsupervised Classification

 

The classified map of Germantown, showing land cover/a degree of land use based on ERDAS extrapolation of manually selected signatures. The Distance map shows areas where the classification may be uncertain.

This week's lab focused on conducting feature classification on aerial imagery using a computer-driven tool (unsupervised) and classification based on analyst inputs (supervised). Both methods require manual retooling before or after, and adjustment and manual assessment of the band representations to check that all features are displayed as clearly as possible. In particular, I used histograms and spectral plots to check for spectral confusion in the pixels I had classified - this is where one pixel may have a value that has been classified in two groups at the same time. At the end, I ran the entire process on an image from Germantown, Maryland, to practice supervised classification and the resulting recoding and display of land cover in Germantown.