Remote assessment of benthic substrate composition in shallow waters using multispectral reflectance

We investigated the utility of quantifying percent coverage of benthic substrate constituents from surface multispectral reflectance measurements. Six substrates were considered: kelp, eelgrass, clay, silt, mineralic sand from a temperate environment, and turtlegrass and carbonate sand from a tropical environment. Each had a unique albedo spectrum that contributes differently to the upward light field in an optically shallow environment. Simplifications to the radiative transfer equation yield an analytic solution for surface reflectance in optically shallow environments. The objectives were to test the inverse model to predict bottom albedo from measurements of surface reflectance, diffuse attenuation, and water depth in the turbid water of eastern Long Island Sound, Connecticut, and clear waters off Exuma, Bahamas. A linear mixing model was used to deconvolve the derived albedo spectra into contributions by the six constituents. The inverse and deconvolution models accurately identified the dominant substrate in the six homogeneous habitats (single point determinations) and predicted the gradient in substrate composition along transects. This approach has applications to benthic survey mapping, habitat assessment, and habitat monitoring.