Unmanned Aerial Systems
Unmanned aerial systems provide a stable means of measuring reef environments beneath the ocean surface. They can greatly expand the geographical coverage of marine datasets with increased safety, data timeliness and affordability, and less environmental impact, than human-based collection methods.
AIMS is certified by the Civil Aviation Safety Authority to operate unmanned aerial vehicles and is harnessing the technology to improve data acquisition efficiency and data quality for scientists, government agencies and industry clients.
In partnership with Boeing, AIMS is investigating the use of medium-range unmanned aerial systems to collect environment data across Australian tropical waters. High-quality imagery acquired on broad-scale surveys supports seabed habitat mapping, modelling and classification, monitoring, and potentially 3-D reef reconstructions. The integration of new sensors such as hyperspectral cameras on routine surveys will provide deeper insights into the health and biodiversity of marine systems.
AIMS has deployed short-range multicopters (pictured) to survey large areas of marine estate. AIMS is also investigating the use of larger, medium-range unmanned aerial systems to provide further insights into broad-scale reef health in a cost-effective way. (Image: E. Matson. Multicopter used in collaboration with QUT.)
AIMS has also used short-range unmanned aerial systems to survey marine debris on coasts, islands and reefs, support dredging work, detect coral bleaching and discover shipwrecks. Further applications include:
- monitoring the performance of underwater vehicles and locating malfunctioning autonomous underwater systems ;
- inspecting off-shore research stations and towers for certification compliance and post-cyclone damage;
- flood plume mapping; and
- dispersal-footprint tracking in the event of ship groundings and oil well blow-outs.
Aerial drone image mosaics are a highly effective way of surveying large areas of reef and capturing additional information that was not previously possible. Here, Myrmidon Reef (on the central Great Barrier Reef) is shown using showing normal images (left) and image-derived depth (right).