Directed ground survey for improved maximum likelihood classification of remotely sensed data

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Abstract
Typicalities of class membership generated from a maximum likelihood classification may be used to increase classification accuracy by the modification of class allocation on the basis of additional ground surveys. Whilst this increases the amount of ground survey required the additional survey effort is directed to regions where there is potential misclassification. Directing surveys to those cases which displayed, for instance, a typicality of less than 0·05 to their most likely class of membership increased significantly the accuracy of a crop classification with synthetic aperture radar data by 11·70 per cent to 77·27 per cent.

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