Derivation of high-resolution bathymetry from multispectral satellite imagery: a comparison of empirical and optimisation methods through geographical error analysis

Hamylton, Sarah M., Hedley, John D., and Beaman, Robin J. (2015) Derivation of high-resolution bathymetry from multispectral satellite imagery: a comparison of empirical and optimisation methods through geographical error analysis. Remote Sensing, 7 (12). pp. 16257-16273.

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Abstract

The high importance of bathymetric character for many processes on reefs means that high-resolution bathymetric models are commonly needed by marine scientists and coastal managers. Empirical and optimisation methods provide two approaches for deriving bathymetry from multispectral satellite imagery, which have been refined and widely applied to coral reefs over the last decade.

This paper compares these two approaches by means of a geographical error analysis for two sites on the Great Barrier Reef: Lizard Island (a continental island fringing reef) and Sykes Reef (a planar platform reef). The geographical distributions of model residuals (i.e., the difference between modelled and measured water depths) are mapped, and their spatial autocorrelation is calculated as a basis for comparing the performance of the bathymetric models.

Comparisons reveal consistent geographical properties of errors arising from both models, including the tendency for positive residuals (i.e., an under-prediction of depth) in shallower areas and negative residuals in deeper areas (i.e., an over-prediction of depth) and the presence of spatial autocorrelation in model errors.

A spatial error model is used to generate more reliable estimates of bathymetry by quantifying the spatial structure (autocorrelation) of model error and incorporating this into an improved regression model. Spatial error models improve bathymetric estimates derived from both methods.

Item ID: 41570
Item Type: Article (Research - C1)
ISSN: 2072-4292
Keywords: coral reef; landscape; WorldView-2; water depth; spatial error; Great Barrier Reef; Lizard Island; Sykes Reef
Additional Information:

This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Funders: University of Wollongong, Lizard Island Research Station
Date Deposited: 10 Dec 2015 02:53
FoR Codes: 04 EARTH SCIENCES > 0403 Geology > 040305 Marine Geoscience @ 100%
SEO Codes: 96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960808 Marine Flora, Fauna and Biodiversity @ 100%
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