High resolution mapping and classification of oyster habitats in nearshore Louisiana using sidescan sonar

Estuaries
By: , and 

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Abstract

Sidescan sonar holds great promise as a tool to quantitatively depict the distribution and extent of benthic habitats in Louisiana's turbid estuaries. In this study, we describe an effective protocol for acoustic sampling in this environment. We also compared three methods of classification in detail: mean-based thresholding, supervised, and unsupervised techniques to classify sidescan imagery into categories of mud and shell. Classification results were compared to ground truth results using quadrat and dredge sampling. Supervised classification gave the best overall result (kappa = 75%) when compared to quadrat results. Classification accuracy was less robust when compared to all dredge samples (kappa = 21-56%), but increased greatly (90-100%) when only dredge samples taken from acoustically homogeneous areas were considered. Sidescan sonar when combined with ground truth sampling at an appropriate scale can be effectively used to establish an accurate substrate base map for both research applications and shellfish management. The sidescan imagery presented here also provides, for the first time, a detailed presentation of oyster habitat patchiness and scale in a productive oyster growing area.
Publication type Article
Publication Subtype Journal Article
Title High resolution mapping and classification of oyster habitats in nearshore Louisiana using sidescan sonar
Series title Estuaries
DOI 10.1007/BF02693925
Volume 28
Issue 3
Year Published 2005
Language English
Contributing office(s) National Wetlands Research Center
Description p. 435-446
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Estuaries
First page 435
Last page 446
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