Accuracy Assessment Paper

Accuracy assessment is an important final step of the classification process. The goal is to quantitatively determine how effectively pixels were groups into the correct land cover classes.
The procedure is relatively simple. Pixels are randomly selected throughout the image using a specified random distribution method. Then the analyst uses the original image along with ancilliary information such as aerial photographs or direct field observation to determine the true land cover represented by each random pixel. This ground truth is compared with the classsification map. If the ground truth and classification match, then the classification of that pixel was accurate. Given that enough random pixels are checked, the percentage of accurate pixels gives a fairly good estimate of the accuracy of the whole map. A more rigorous and
An error matrix is simply an array of numbers indicating how many pixels were associated with each class both in terms of the classification and the ground truth (Jensen 247).
I performed an accuracy assessment of my land cover classification map in ERDAS, which generated the accuracy report shown below. In order to save time, I only used 50 random points total, but it is recommended that you have 50 points per class, which would have been
300 in my case. Thus, the information below could probably be improved upon, but it is sufficient for the scope of this project. Another source of error in this information is that I only used the original image to determine the ground truth, which would be more accurate with