Retrieving key benthic cover types and bathymetry from hyperspectral imagery

Wojciech M. Klonowski; Peter R.C.S. Fearns; Mervyn J. Lynch

doi:10.1117/1.2816113

1 December 2007 Retrieving key benthic cover types and bathymetry from hyperspectral imagery

Wojciech M. Klonowski, Peter R.C.S. Fearns, Mervyn J. Lynch

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 1, Issue 1, 011505 (December 2007). https://doi.org/10.1117/1.2816113

Abstract

Bathymetry and the spatial distribution of benthic cover in coastal waters are of key importance in managing and monitoring our coastal water environments. Currently very little of the Western Australian shallow coastal water habitats are mapped, and for those maps that do exist, the spatial resolution generally is poor and the information is dated. Aircraft and space-borne hyperspectral sensors have been shown to be useful in imaging substrate features in shallow coastal waters. This paper describes a method for quantitatively estimating both bathymetry and benthic cover in shallow waters from hyperspectral imagery. The method incorporates a shallow water reflectance model, which accounts for the water column absorption and backscattering, water depth and substrate reflectance. The model was tested against simulated reflectance data, demonstrating the models' ability to retrieve appropriate fractional coverage of sediment, sea grass and brown algae for depths ranging from 1 - 12 m. The model was applied to a HyMap image encompassing a portion of the Jurien Bay Marine Park off the coast of Western Australia. The retrieved benthic cover products were compared to underwater video observations sampled within the image. The comparison shows the method's great potential for characterizing key aspects of marine ecosystems from remotely sensed hyperspectral data.

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Wojciech M. Klonowski, Peter R.C.S. Fearns, and Mervyn J. Lynch "Retrieving key benthic cover types and bathymetry from hyperspectral imagery," Journal of Applied Remote Sensing 1(1), 011505 (1 December 2007). https://doi.org/10.1117/1.2816113

Published: 1 December 2007

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