Estimating the coverage of coral reef benthic communities from airborne hyperspectral remote sensing data: multiple discriminant function analysis and linear spectral unmixing

Abstract

A staged approach for the application of linear spectral unmixing techniques to airborne hyperspectral remote sensing data of reef communities of the Al Wajh Barrier, Red Sea, is presented. Quantification of the percentage composition of four different reef components (live coral, dead coral, macroalgae and carbonate sand) contained within the ground sampling distance associated with an individual pixel is demonstrated. In the first stage, multiple discriminant function analysis is applied to spectra collected in situ to define an optimal subset combination of derivative and raw image wavebands for discriminating reef benthos. In the second phase, unmixing is applied to a similarly reduced subset of pre-processed image data to accurately determine the relative abundance of the reef benthos (R 2 > 0.7 for all four components). The result of a phased approach is an increased signal-to-noise ratio for solution of the linear functions and reduction of processing burdens associated with image unmixing.