Accuracy Assessment | Kappa Coefficient | User Accuracy| Producer Accuracy| Overall Accuracy

Today I'll show how to do Accuracy Assessment of a classified Landsat Image.
Accuracy Assessment uses a Reference Dataset to determine the accuracy of your classified result. The values of your reference dataset need to match the schema. The most common way to assess the accuracy of a classified map is to create a set of random points from the ground truth data and compare that to the classified data in a confusion matrix. Although this is a two-step process, you may need to compare the results of different classification methods or training sites, or you may not have ground truth data and are relying on the same imagery that you used to create the classification.
Accuracy Assessment Formula
Users Accuracy=(Number of Correctly Classified Pixels in each Category)/(Total number of Classified Pixels in that Category (The Row Total))×100
Producer Accuracy=(Number of Correctly Classified Pixels in each Category)/(Total Number of Reference Pixels in that Category (The Column Total))×100
Overall Accuracy=(Total Number of Correctly Classified Pixels (Diagonal))/(Total Number of Reference Pixels)×100
Kappa Coefficient (T)=((TS×TCS)-∑(Column Total×Row Total))/(TS^2-∑(Column TotalxRow Total))×100
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