Application of eigenvector analysis to remote sensing of coastal water quality

Abstract

The use of algorithms incorporating radiance information from one or a number of wavelengths is a standard technique for detecting the concentration and distribution of water quality parameters in coastal and open ocean waters. It has become clear, however, that in a turbid dynamic coastal environment there is no one algorithm applicable for all times, seasons or area because the composition of the suspended material variescontinually. Consequently site specific algorithms have been proposed. Results of an eigenvector analysis of radiance spectra and sea-truth data collected as part of airborne remote sensing campaigns in 1984 and 1985 are presented. The eigenvectors of radiance data are shown to be dependent on the type and relative concentrations of material in suspension. The technique is shown to have great potential for the identification of the composition of material in suspension without recourse to sea-truth data. This information could be used as a criterion for selection of an appropriate algorithm.