Modern hyper- and ultra- spectral remote sensors are capable of providing spectra with thousands of channels. These channels are not independent of each other. We will analyze the information content of the hyperspectral data using principal component analysis. We will show that the information content of the original spectrum is conserved by Empirical Orthogonal Function (EOF) transformations. A radiative transfer model and a physical inversion algorithm based on principal component analysis will be presented.
© 2009 Optical Society of AmericaPDF Article