POSTER Session 2

Tuesday, October 8
11:30–13:10

Poster Session | 1 | 2 | 3 | 4InstructionsSchedule at a Glance

ABSTRACT 962 | POSTER T-054

DEPENDENCE OF CORAL REEF REMOTE SENSING RETRIEVALS ON WATER DEPTH, WATER OPTICAL PROPERTIES, AND CORAL FRACTION

Many algorithms for remote sensing of the shallow seafloor use a simplified reflectance model. Water-leaving reflectance is an analytical function of water optical properties, water depth, and a reflecting bottom. In some cases, the water optical properties and bottom reflectance are themselves derived through bio-optical models. Retrieval proceeds by finding the combination of those parameters that provides the best fit against an unknown remotely sensed signal. Algorithm results are often promising, but it is also often the case that these optimized fits do not completely capture variability present in the remote sensing spectrum. The aim of this study is to evaluate, specifically for coral reefs, the relative dependence of retrievals on each of the parameters in the simple model: diffuse attenuation (K), diffuse backscatter (bbd), water depth (H), and benthic cover of coral relative to algae (driving differences in bottom reflectance, Rb). Based on 48,400 Hydrolight radiative transfer simulations, retrievals have the greatest dependence on H, regardless of water clarity or coral fraction. Retrievals have moderate dependence on K and bbd, increasing with greater water depth. Dependence on coral fraction is minimal, even at very shallow depths. This is key, because coral fraction is the true parameter of interest to coral reef science. These trends explain inaccuracies often encountered in coral reef remote sensing. To overcome the lack of dependence on coral fraction, it is necessary to increase sensitivity to the well-established but subtle spectral features that discriminate coral from other reef organisms and substrates.

Eric Hochberg, Bermuda Institute of Ocean Sciences, Bermuda, https://orcid.org/0000-0001-5400-9252

Poster Session | 1 | 2 | 3 | 4 |
InstructionsSchedule at a Glance

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