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An Acoustic Ground Discrimination System (AGDS) can extract information on the nature of the seabed. Compared to satellite or airborne sensors, AGDS is rarely used in tropical environments but is easy to operate and produces a modest amount of digital data. This study aimed to assess acoustic surveys of coral reef benthic classes using a RoxAnn 2 AGDS in the Philippines. Benthic classes were categorised into four levels of detail using hierarchical classification of field data. Using independent data, subsequent maps were shown to have overall accuracies of: 85% at coarse resolution (three classes), 61% and 54% at two intermediate levels (five and four classes) and 28% at fine resolution (10 classes). These accuracies are assumed to be conservative because of constraints during this study including semi-quantitative data for discriminating class types, benthic changes between AGDS and accuracy assessment surveys and lack of differential global positioning system (GPS). Despite these limitations, AGDS accuracy levels were comparable to those achieved by satellites and it has advantages including greater water penetration and independence from cloud cover. Acoustic data are, therefore, proposed as useful tools for tropical habitat mapping and complementary to satellite and airborne sensors.

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Spatial surveys of marine benthic habitats and biota based on the interpretation of acoustic data were carried out at two sites in the eastern English Channel each representing different scales of geographic area and intensity of survey. A small area (4×12 km) crossing the Hastings Shingle Bank was surveyed at a relatively high intensity (track spacing 400 m) and was nested within a larger area between Hastings and Dungeness (12×40 km), which was surveyed at a lower intensity (track spacing 2 km). Surveys were conducted with two acoustic ground discrimination systems (AGDS), RoxAnn and QTC-VIEW and the primary purpose of the investigation was to compare the performance of the two AGDS using a common approach to analysis of the different data outputs (E1 and E2 for RoxAnn and the Q eigenvectors from QTC-VIEW). Exploratory data analysis using variography indicated that interpolation between tracks was justified for the smaller site to create a complete coverage, but was limited to the creation of a digital image of the track data for the larger area. Grab and video sample data were available for supervised classification of the AGDS data and interpreted sidescan images for comparison with unsupervised classification. Both AGDS gave similar outputs, although RoxAnn consistently gave slightly better levels of performance than QTC-VIEW as measured using error matrices. Although the investigation was not designed to compare the performance of AGDS and sidescan, the outputs from AGDS were similar to the visual interpretation of the sidescan sonar data. It was concluded that despite the inherent limitations of AGDS, they may be suitable for providing distribution maps at a broad scale that can give a context for the interpretation of finer scale survey of smaller, nested areas.