Comparison of RoxAnn and QTC-View acoustic bottom classification system performance for the Cairns area, Great Barrier Reef, Australia

Comparisons are made between bottom categorisations obtained by the RoxAnn and QTC-View (version 4) acoustic bottom classification systems in the Grea t Barrier Reef lagoon, Australia. RoxAnn classification is based on energy calculations for first and second echosounder returns, while QTC version 4 calculates first echo shape parameters. QTC provides automatic classificati ons and confidence estimates, whereas RoxAnn relies on arbitrary manual cal ibration. QTC bottom classes generally had consistent grain size and textur e properties, and followed grainsize trends, but RoxAnn classes were diffic ult to define. QTC classes mapped to well-defined parallelograms in RoxAnn space, indicating with other considerations that the concept of "RoxAnn squ ares" for RoxAnn calibration is not optimal. RoxAnn performance was strongl y dependent on ship speed, but QTC was not. The RoxAnn ship speed dependenc e was a major limitation, which appears to have primarily affected the low- energy second echo. Both systems experienced problems over rough terrain wh ich could sometimes be monitored by simple depth correlations. The acoustic systems provide useful information, but are not suitable for full stand al one usage. Bottoms should also be classified with conventional techniques, after which acoustic data can be used to fill in the gaps, but with ambigui ties; or to indicate areas needing further sampling. Despite the shortcomin gs of RoxAnn, there are indications it could be used as a remote sensor for bottom porosity and related parameters. (C) 1999 Elsevier Science Ltd. All rights reserved.