Visualization of uncertainty in LANDSAT classification process

Many uncertainties can be found in the classification of remotely sensed data. Namely they can arise in defining classification classes. We use two ways, incorporating acquired Corine Land Cover labels and our manually annotated labels. We are describing several visualization possibilities to demonstrate uncertainties in labels and their connections with classification results. We use parallel coordinates to visualize data, presenting problems in classes definitions. These failures can be consequently seen in the results of classification in confusion matrix. We inspect also posterior probabilities of k-Nearest Neighbor (k-NN) classifier visualizing maximum likelihood class probabilities as alpha channel of resulting classification map.