Your access to the IMOS AUV data discovery and exploration is through the Australian Ocean Data Network (AODN) Portal.
The data streams provided are suitable for observational changes in benthic communities that can be related to climate change, climate variability, and human activities. The program in designed with a particular focus on reef habitats because reefs support long-lived organisms that are sensitive to environmental change as they are unable to relocate once established.
A program of repeat monitoring can observe changes in the environmental conditions that are likely to have a pronounced impact on these reefs. The precisely registered maps generated by the AUV, collected at regular intervals, are providing researchers with the baseline ecological data necessary to make quantitative inferences about the long-term effects of climate change and human activities on the benthos. In the short term, the facility will also provide stakeholders with data useful for the effective management of marine parks and fisheries where the benthos provides a food source or plays a role in the life cycle of the target species.
Each of the high resolution imaging missions are typically flown at a fixed altitude above the seafloor. Data collected by the AUV consists of stereo imagery, multibeam sonar, vehicle navigation and water chemistry observations. All data products are precisely georeferenced using state-of-the art terrain-aided navigation algorithms. Optical imagery is delivered as individual high resolution, colour corrected images (geotiffs) and also in processed form, as mosaics and 3D seafloor reconstructions.
An AUV Images Viewer Tool has been developed to facilitate the exploration and management of AUV data by the AODN and AUV Facilities.
To create dense three-dimensional textured maps for Scott Reef, Western Australia (below) the AUV completed 50 reciprocal track lines covering an area of 50 m x 75 m over the edge of a deepwater reef. The AUV collected in the order of 10,000 stereo image pairs during the course of this dive. A visual simultaneous localisation and mapping (SLAM) algorithm is used to identify the loop closures to refine the vehicle’s estimated trajectory. The estimated vehicle trajectory is then used to generate a detailed, 3-D, texture-mapped surface model of the survey site.