Research projects

Recent increases in the spatial coverage and temporal resolution of 40 m resolution Synthetic Aperture Radar (SAR) imagery, is opening new opportunities to rapidly detect environmental observations e.g. ice sheet and iceberg position with greater positional accuracy. Our team are developing supervised and unsupervised machine learning techniques to automatically detect sea ice and iceberg position from Sentinel-1 SAR imagery.

In the AI for smart conservation project, BAS are collaborating with local ecologists and conservation agencies to develop decision-making tools informed by sea ice forecasts. By combining satellite observations, GPS …

AMOP is developing Artificial Intelligence methods that aim to optimise the efficiency of Antarctic field operations, while maximising science delivery

Environmental research relies on digital infrastructure (hardware, software and methods) to provide services that help researchers answer questions about the environment around us, and innovators to work out ways that …

Digital Twinning is next generation technology for data fusion and computer modelling enabling us to rapidly get answers to “what-if” questions. Digital Twins (DTs) are already in operation in industry …

IceNet is a probabilistic, deep learning sea ice forecasting system developed by an international team and led by British Antarctic Survey and The Alan Turing Institute [Andersson et al., 2021]. …