Uncertainty GIS Report

1. UNCERTAINTY IN
GEOSPATIAL DATA
By : Ehsan Hamzei (810392121)

2. GOAL
• We want to Learn about Uncertainty Factor in Raster Model.
• All of them derived from “Confusion Matrix” (or Ambiguity Matrix).

3. CONFUSION MATRIX

4. OMISSION - COMMISSION
• Error of omission ( Producer’ s acc.) :
• proportion of values in reality, which were interpreted as something else: Sum of
column’s non-diagonal elements / column total (For Corn 8/20)
• Error of commission (User’s acc.) :
• proportion of values which were in reality found to belong to another class: Sum of row’s
non-diagonal elements / row total (For Corn 6/18)

5. TOTAL ACCURACY
• Also called: Correct Classification Rate!
• Formulas: TA = (a + d)/N
• Where N = a + b + c + d

6. LIMITATION OF TOTAL ACCURACY
• Consider a 2-class problem
• Number of Class 0 examples = 9990
• Number of Class 1 examples = 10
• If model predicts everything to be class 0, accuracy is 9990/10000 = 99.9 %
• Accuracy is misleading because model does not detect any class 1 example

7. COHEN’ KAPPA
• Formulas: [(a + d)- (((a + c)(a + b) + (b + d)*(c + d))/N)]/[N - (((a + c)(a + b) + (b + d)(c
+ d))/N]

8. OTHER FACTORS

9. OTHER FACTORS

10. THANKS…