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Remote Sensing Classification Accuracy. 1. Select Test Areas. Selecte test areas in an image to evaluate the accuracy of a classification Test areas should be representative categorically and geographically Sampling methods: uniform wall-to-wall, random, stratified random sampling

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1 select test areas
1. Select Test Areas
  • Selecte test areas in an image to evaluate the accuracy of a classification
  • Test areas should be representative categorically and geographically
  • Sampling methods: uniform wall-to-wall, random, stratified random sampling
  • Sample size: 50 - 100 pixels each category
2 error assessment
2. Error Assessment
  • A classification is not complete until its accuracy is assessed
  • Error matrix
  • KHAT statistics
error matrix
Error Matrix
  • Also called confusion matrix and contingency table
  • Compares the ground truth and the results of the classification for the test areas
  • Can be used to evaluate the result of classifying the training set pixels and the results of classifying the actual full-scene
error matrix7

ClassifiedReference DataDataWater  Sand  Forest   Urban    Corn Hay Row Total

Water480 0 5 0 0 0 485

Sand 0 52 0 20 0 0 72

Forest        0 0 313  40 0 0 353Urban 0 16 0 126 0 0 142

Corn 0 0 0 38 342 79 459

Hay 0 0 38 24 60 359481

Col Total  480       68     356 248 402 4381992

Error Matrix

Diagonal cells are correctly classified pixels

                            correctly classified pixels 1672

Overall accuracy =  ------------------------------- = ------- = 84%                               total pixels evaluated 1992

error matrix8

ClassifiedReference DataDataWater  Sand  Forest   Urban    Corn Hay Row Total

Water480 0 5 0 0 0 485

Sand 0 52 0 20 0 0 72

Forest        0 0 313  40 0 0 353Urban 0 16 0 126 0 0 142

Corn 0 0 0 38 342 79 459

Hay 0 0 38 24 60 359481

Col Total  480       68     356 248 402 4381992

Error Matrix

In this case, the non-diagonal column cells are omission errors

e.g. omission error for forest = 43/356 = 12%

The non-diagonal row cells are commission errors

e.g. commission error for corn 117/459 = 25%

error matrix9

ClassifiedReference DataDataWater  Sand  Forest   Urban    Corn Hay Row Total

Water480 0 5 0 0 0 485

Sand 0 52 0 20 0 0 72

Forest        0 0 313  40 0 0 353Urban 0 16 0 126 0 0 142

Corn 0 0 0 38 342 79 459

Hay 0 0 38 24 60 359481

Col Total  480       68     356 248 402 4381992

Error Matrix

correctly classified in each category producer\'s accuracy =  ----------------------------------------------                           the total pixels used in the category (col total)

Omission error = 1 (100%) - producer\'s accuracy

error matrix10

ClassifiedReference DataDataWater  Sand  Forest   Urban    Corn Hay Row Total

Water480 0 5 0 0 0 485

Sand 0 52 0 20 0 0 72

Forest        0 0 313  40 0 0 353Urban 0 16 0 126 0 0 142

Corn 0 0 0 38 342 79 459

Hay 0 0 38 24 60 359481

Col Total  480       68     356 248 402 4381992

Error Matrix

          correctly classified in each category user\'s accuracy =  -------------------------------------------------------                         the total pixels used in the category (row total)

Commission error = 1 (100%) - user\'s accuracy

khat statistics
KHAT Statistics
  • A measure of the difference between the actual agreement between reference data and the results of classification, and the chance agreement between the reference data and a random classifier
khat statistics14
KHAT Statistics

^      observed accuracy - chance agreement k  = --------------------------------------------------              1 - chance agreement

  • The KHAT value usually ranges from 0 to 1
  • 0 indicates the classification is not any better than a random assignment of pixels
  • 1 indicates that the classification is 100% improvement from random assignment
khat statistics15
KHAT Statistics

r          r       N × S xii -  S (xi+  ×  x+i) ^         i=1       i=1k = ----------------------------------- r           N2  -  S (xi+  ×  x+i) i=1

r - number of rows in the error matrix

xii - number of obs in row i and column i (the diagonal cells)

xi+ - total obs of row i

x+i - total obs of column i

N - total of obs in the matrix

khat statistics17
KHAT Statistics
  • KHAT considers both omission and commission errors
readings
Readings
  • Chapter 7
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