COASTAL BATHYMETRY FROM HYPERSPECTRAL REMOTE SENSING DATA: COMPARISONS WITH HIGH RESOLUTION MULTIBEAM BATHYMETRY

Abstract

We present a large-scale quantitative test of a hyperspectral remote-sensing reflectance algorithm. We show that coastal bathymetry can be adequately derived through model inversions using data from the Airborne Visible-Infrared Imaging Spectrometer instrument. Data are analyzed from a shore-perpendicular transect 5 km offshore Sarasota, Florida at water depths ranging from 10 m to 15.5 m. Derived bottom depths are compared to a high-resolution multibeam bathymetry survey. Model-derived depths are biased 4.9% shallower than the mean of the multibeam depths with an RMS error of 7.83%. These results suggest that the model performs well for retrieving bottom depths from hyperspectral data in subtropical coastal areas in water depths ranging from 10 m to 15.5 m.