This two-day advanced course teaches students how to perform both unsupervised and supervised classification, optimizing the accuracy of land cover maps. The class will incorporate ancillary data such as aerial photography, GPS data and ground truth surveys.

• Perform both unsupervised and supervised classification, optimizing the accuracy of land cover maps
• Incorporate ancillary data such as aerial photography, GPS data and ground truth surveys
• Perform unsupervised classification routines and attribute manipulation
• Define training signatures using AOIs and vector data
• Manipulate supervised signatures within the signature editor
• Evaluate supervised signatures statistically and graphically
• Collect and evaluate signatures using feature space images
• Apply a land cover classification decision rule to an image
• Evaluate and enhance the classification with the threshold and masking utilities
• Perform an accuracy assessment of the classification using ground survey data
• Address confused classes with Spatial Modeler