Uncertainty in Hyperspectral Remote Sensing: Analysis of the Potential and Limitation of Shallow Water Bathymetry and Benthic Classification

Abstract

Propagating the inherent uncertainty in hyperspectral remote sensing is key in understanding the limitation and potential of derived bathymetry and benthic classification. Using an improved optimisation algorithm, the potential of detecting temporal bathymetric changes above uncertainty was quantified from a time series of hyperspectral imagery. A new processing approach was also developed that assessed the limitations and potential of benthic classification by analysing optical separability of substrates above total system uncertainty and attenuating water column.