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A Review of Three Discrete Multivariate Analysis Techniques Used in Assessing the Accuracy of Remotely Sensed Data from Error Matrices

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2 Author(s)
Congalton, R.G. ; Department of Forestry and Resource Management, University of California, Berkeley, CA 94720 ; Mead, R.A.

Three discrete multivariate analysis techniques were used to assess the accuracy of land use/land cover classifications generated from remotely sensed data. Error matrices or contingency tables were analyzed using these techniques and the results reported. The first technique is a normalization procedure using an "iterative proportional fitting" algorithm that allows for direct comparison of Corresponding cell values in different matrices irregardless of sample size. The second technique provides a method of testing for significant differences between error matrices that vary by only a single variable or factor. The third technique allows for multivariable comparisons to be made between matrices. Each technique is implemented through the use of a computer program.

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:GE-24 ,  Issue: 1 )