Abstract
This paper describes how principal components analysis and Tasseled Cap Transformation were used in the Landsat ETM+ images of south-east London. The six-dimensional landsat dataset was reduced to three major components where the first component contributed for the maximum proportion of the variance of the original dataset, and subsequent orthogonal components accounted for the maximum proportion of the remaining variance. The first PCA component showed urban settings in the first component, vegetation in the second and water in the third. Similar to the PCA, the TC showed the urban settings in the brightness component, vegetation in greenness and water in the wetness component. As compared to the PCA, TC transformation has a more analytical basis as it combines a generalization from empirical observations. The PCA and TC components were compared to each other which showed that PC1 contained more brightness information than TC1. However, TC2 and TC3 included pertinent information than PC2 and PC3. The colour composites PCA123 and TC123 were visually compared which showed that for this study, TC123 produced better results.
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