Abstract

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 America

PDF Article

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription