Annualmeeting:2017 CSDMS meeting-088


Browse  abstracts

An algorithm for optically-deriving water depth in coral reef landscapes in the absence of ground-truth data

Jeremy Kerr, Nova Southeastern University Dania Florida, United States.
Sam Purkis, University of Miami - RSMAS Miami Florida, United States.

[[Image:|300px|right|link=File:]]Although numerous approaches for deriving water depth from bands of remotely-sensed imagery in the visible spectrum exist, digital terrain models for remote tropical carbonate landscapes remain few in number. The paucity is due, in part, to the lack of in situ measurements of pertinent information needed to tune water depth derivation algorithms. In many cases, the collection of the needed ground-truth data is often prohibitively expensive or logistically infeasible. We present an approach for deriving water depth from multi-spectral satellite imagery without the need for direct measurement of water depth, bottom reflectance, or water column properties within the site of interest. The reliability of the approach is demonstrated for five satellite images, each at a different study site, with overall RMSE values ranging from 0.84 m to 1.56 m when using chlorophyll concentrations equal to 0.05 $\text{mg m}^{-3}$ and a generic seafloor spectrum generated from a spectral library of common benthic constituents. Sensitivity analyses show that the model is robust to selection of bottom reflectance inputs and errors in the atmospheric correction and sensitive to parameterization of chlorophyll concentration.