Accuracy assessment is an important part of any classification project. It compares the classified image to another data source that is considered being accurate or ground truth data. I prepared this presentation for the interactive class of the course "Arcgis and Remote Sensing" organized by the Research Society, Bangladesh.

1. Accuracy Assessment
Presented by
Shacin Chandra Saha
Student of Geology and Mining
University of Barishal
E-mail: shacinsaha91@gmail.com
Phone: +8801871470691
LinkedIn: www.linkedin.com/in/shacin91
Facebook: www.facebook.com/shacin91

2. Accuracy Assessment
It is the comparison between classified image and ground truth data.
 Ground truth can be collected in the field that is time consuming and expensive
and need expensive GPS device.
 Can be derived from high-resolution satellite image or existing classified image.
 Most common way to create a set of random points from the ground truth data and compare
that in a confusion matrix.

3. Confusion Matrix
It is the quantitative method of characterizing image classification accuracy.
It is a table that shows correspondence between the classification result and a reference image.

4. Producer’s Accuracy
It is the percentage of right pixel values and total pixel values of Colum related to reference image.
Producer Accuracy(A) =
Total right pixel values * 100 %
Total pixel values

5. Errors of Commission
It is the percentage of wrong pixel values and total pixel values of Colum related to reference image.
Errors of Commission(A) =
Wrong pixel values * 100 %
Total pixel values

6. User Accuracy
It is the percentage of right pixel values and total pixel values of Row related to Classified image.
User Accuracy (a) =
Total right pixel values * 100 %
Total pixel values

7. Errors of Omission
It is the percentage of wrong pixel values and total pixel values of Colum related to reference image.
Errors of Omission(a) =
Wrong pixel values * 100 %
Total pixel values

8. Overall Accuracy
It is the main proportion measurement that determines how correctly classified.
Overall Accuracy =
Total right pixel values from all Colum and row * 100 %
Total summation pixel values

9. Kappa Coefficient
It is more correct calculation of accuracy than Overall accuracy.
Kappa Coefficient =
(Total summation*Total Correct Summation) – sum(user total*producer total) 100 %
((Total summation)2 – sum(user total* product total))