AN IMPROVED SKIDMORE TURNER CLASSIFIER

A new decision rule significantly improves the classification accuracy of the nonparametric spectral classifier described by Skidmore and Tu rner (1988). The new rule normalizes class histograms with the mean fr equency, rather than with the number of training pixels in a class, an d gives a classifier which consistently outperforms the maximum-likeli hood classifier. Another type of classifier, which combines a two-dime nsional and a one-dimensional Skidmore/Turner (S/T) classifier, has hi gher classification accuracies than the S/T classifier with the improv ed decision rule, in two of four study areas. Tree species were classi fied for two study areas and land-cover classes for the other two.