A review of assessing the accuracy of classifications of remotely sensed data

Remote Sensing of Environment

Volumn 37, Issue 1, 1991, Pages 35-46

  Congalton, Russell G ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION; CONTINGENCY TABLE; SAMPLING; SPATIAL AUTOCORRELATION;

EID: 0026278621     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/0034-4257(91)90048-B     Document Type: Article

References (25)

1. A land use and land cover classification system for use with remote sensor data
2. The minimum accuracy value as an index of classification accuracy
3. Advances in forest inventory using advanced digital imagery
4. Spatial autocorrelation effects upon the accuracy of supervised classification of land cover
5. Using cluster analysis to improve the selection of training statistics in classifying remotely sensed data
6. A coefficient of agreement for nominal scales
7. Using spatial autocorrelation analysis to explore errors in maps generated from remotely sensed data
8. A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data
9. Assessing Landsat classification accuracy using discrete multivariate statistical techniques
10. Comparison of sampling procedures and data analysis for a land-use and land-cover map
11. Testing land-use map accuracy: another look
12. Sampling designs to test land-use map accuracy
13. Land use map accuracy criteria
14. Correct formulation of the kappa coefficient of agreement
15. Satellite data: management panacea of potential problem?
16. Digital image analysis techniques for natural resource inventory
17. Analysis of variance of thematic mapping experiment data
18. A coefficient of agreement as a measure of thematic classification accuracy
19. Sampling for thematic map accuracy testing
20. Assessing the accuracy of resource inventory maps
21. Accuracy assessment: a user's perspective
22. Testing land use map accuracy