GILES FOODY giles.foody@nottingham.ac.uk
Professor of Geographical Information
Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification
Foody, Giles M.
Authors
Abstract
The kappa coefficient is not an index of accuracy, indeed it is not an index of overall agreement but one of agreement beyond chance. Chance agreement is, however, irrelevant in an accuracy assessment and is anyway inappropriately modelled in the calculation of a kappa coefficient for typical remote sensing applications. The magnitude of a kappa coefficient is also difficult to interpret. Values that span the full range of widely used interpretation scales, indicating a level of agreement that equates to that estimated to arise from chance alone all the way through to almost perfect agreement, can be obtained from classifications that satisfy demanding accuracy targets (e.g. for a classification with overall accuracy of 95% the range of possible values of the kappa coefficient is −0.026 to 0.900). Comparisons of kappa coefficients are particularly challenging if the classes vary in their abundance (i.e. prevalence) as the magnitude of a kappa coefficient reflects not only agreement in labelling but also properties of the populations under study. It is shown that all of the arguments put forward for the use of the kappa coefficient in accuracy assessment are flawed and/or irrelevant as they apply equally to other, sometimes easier to calculate, measures of accuracy. Calls for the kappa coefficient to be abandoned from accuracy assessments should finally be heeded and researchers are encouraged to provide a set of simple measures and associated outputs such as estimates of per-class accuracy and the confusion matrix when assessing and comparing classification accuracy.
Citation
Foody, G. M. (2020). Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification. Remote Sensing of Environment, 239, Article 111630. https://doi.org/10.1016/j.rse.2019.111630
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 28, 2019 |
Online Publication Date | Jan 9, 2020 |
Publication Date | Mar 15, 2020 |
Deposit Date | Jan 8, 2020 |
Publicly Available Date | Jan 10, 2021 |
Journal | Remote Sensing of Environment |
Print ISSN | 0034-4257 |
Electronic ISSN | 1879-0704 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 239 |
Article Number | 111630 |
DOI | https://doi.org/10.1016/j.rse.2019.111630 |
Keywords | Computers in Earth Sciences; Soil Science; Geology |
Public URL | https://nottingham-repository.worktribe.com/output/3690555 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S0034425719306509 |
Additional Information | This article is maintained by: Elsevier; Article Title: Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification; Journal Title: Remote Sensing of Environment; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.rse.2019.111630; Content Type: article; Copyright: © 2020 Elsevier Inc. All rights reserved. |
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