| Remote sensing offers an alternative to diver surveys for the large-scale inventory of benthic macrophytes in the shallow subtidal environment. The goal of this study was to determine the limits of spectral discrimination of benthic macrophytes as a function of depth and water clarity. Bottom reflectance and water column optical properties were measured to predict the capabilities of remote sensing reflectance to distinguish classes of benthic vegetation. These predictions were compared to in situ surface measures of remote sensing reflectance. Bottom reflectance was separated into five optical classes, based on spectral shape and amplitude: fleshy red algae, coralline red algae, brown algae, seagrass, and sand. Characteristic peaks of bottom reflectance were clearly maintained in the remote sensing reflectance spectra at wavelengths below 600 nm and can provide the basis for identification of bottom vegetation from remote sensing reflectance in depths of 2 to 4 meters, depending on water clarity. |
