GIS 4035 Module 4: Accuracy and Ground Truthing

Land use land cover classification of Pascagoula, MS with accuracy of thirty sample points symbolized.

Our task for week 4 of Aerial Photo Interpretation and Remote Sensing was to check the accuracy of last week's efforts to classify an aerial photograph. The best methods for ground truthing such a classification involve direct testing sample sites in the field, but the online nature of the course prevents such tests. Instead, we utilized Google Maps (and especially Street View) to test the classification accuracy of thirty sample sites. I roughly followed a stratified random sampling pattern based on classification category. However, small or homogeneous categories were given fewer samples (e.g., the large body of water in the west, the cemetery) while large, heterogeneous categories were allotted more samples (e.g., residential, commercial and services). The accuracy of my classification turned out to be about 73%. The main error sources were misclassifications of bodies of water and of forest cover. While my misclassification of Krebs Lake as a bay could, perhaps, be forgiven, my misclassifications of forest cover were due to not correctly distinguishing deciduous and evergreen trees. As a result of this assignment, however, I believe I would have a higher accuracy percentage on a similar aerial photo.