Abstract
Abstract In this study Principal Components have been calculated using covariance and correlation matrices for Tour data sets: Monthly NOAA-NDVI maximum-value composites, NOAA-LAC data, Landsat-TM data, and SPOT multi-spectral data. An analysis of the results shows consistent improvements in the signal to noise ratio (SNR) using the correlation matrix in comparison to the covariance matrix in the principal components analysis for all the data sets
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