Artificial Intelligence (AI) Lab

The AI lab applies artificial intelligence to tackle key polar challenges.

Our team analyses data from sources including sea ice, wildlife, and climate models. AI then helps us find patterns and insights in these complex datasets which would be otherwise impossible to detect.

We use AI to make polar research more efficient and sustainable.

Our tools help reduce carbon emissions by optimising travel routes for research ships and autonomous vehicles, and by improving how we collect data in remote locations.

Team Priorities

Monitoring polar regions

We use AI to track and understand changes in ice, oceans, and atmospheric conditions in real time.

Digital twins and models

We create virtual simulations of natural systems. These digital copies let us test different scenarios and predict future changes safely.

Automated mission planning

AI optimises expedition schedules and decides where to place scientific instruments. This saves time, money, and reduces environmental impact.

Faster climate models

We integrate data into models that provide more accurate climate predictions more quickly.

AI data pipelines

We build tools that transform large, complex datasets into formats that people can actually use.

Technology and training

We develop practical AI solutions for satellite observations, sensor networks, and polar logistics. Our PhD and student projects train the next generation of environmental AI scientists.

International collaboration

We partner with research organisations worldwide to develop AI methods for polar science.

Supporting decision-makers

Our AI tools provide actionable information to policymakers, satellite operators, and conservation organisations.

Public engagement

We share our research through media and public talks.

Featured Project

Machine Learning for Seasonal Sea Ice Forecasting

8 April, 2022

IceNet is a deep learning system that forecasts Arctic sea ice. The system is trained on climate simulations and observational data. It outperforms state-of-the-art dynamical models, especially for extreme sea ice events.

1. Logist AI for environmentally aware decision support

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

   Read more of: Logist AI for environmentally aware decision support

   

2. Machine Learning for Sea Ice Forecasting

   IceNet is a deep learning system that forecasts Arctic sea ice. The system is trained on climate simulations and observational data. It outperforms state-of-the-art dynamical models, especially for extreme sea ice events.

   Read more of: Machine Learning for Sea Ice Forecasting

   

3. AI for smart conservation

   The AI for smart conservation project combines sea ice forecasts, satellite data, and GPS tracking to create early-warning systems for Arctic wildlife.

   Read more of: AI for smart conservation

   

4. AI for Earth Observation

   The AI for Earth Observation project develops machine learning tools to detect icebergs, sea ice, and wildlife from satellite imagery.

   Read more of: AI for Earth Observation

   

5. Digital Twins of the Polar Regions

   This project is developing digital twins of Antarctic and Arctic environments and resources. A digital twin makes it possible to test “what if” questions far more quickly than traditional computer models.

   Read more of: Digital Twins of the Polar Regions

   

6. DI4EDS

   A British Antarctic Survey initiative bringing together technology service providers to develop adaptable, reusable digital tools.

   Read more of: DI4EDS

   

1. Using AI to track icebergs

   Researchers are using a new AI tool to detect icebergs in the Southern Ocean – the first step towards tracking the complete lifecycle of Antarctic icebergs from satellite data.

   Read more of: Using AI to track icebergs

   

2. AI tool to revolutionise polar ship navigation

   Artificial Intelligence (AI) will enable ships navigating in polar ocean conditions to be more efficient using a new route planning tool created by British Antarctic Survey (BAS) researchers. The tool […]

   Read more of: AI tool to revolutionise polar ship navigation

   

3. Space technology and artificial intelligence to monitor whale mass stranding events

   An international team of scientists led by British Antarctic Survey have published research today on using new technology to study mass stranding of whales from space and how the technology […]

   Read more of: Space technology and artificial intelligence to monitor whale mass stranding events

   

4. Artificial intelligence to help predict Arctic sea ice loss

   A new AI (artificial intelligence) tool is set to enable scientists to more accurately forecast Arctic sea ice conditions months into the future. The improved predictions could underpin new early-warning […]

   Read more of: Artificial intelligence to help predict Arctic sea ice loss

   

5. Using AI to track whales from space

   British Antarctic Survey (BAS) scientists will work with an Artificial Intelligence company after being awarded a contract from the Canadian Space Agency (CSA) to support the protection of an endangered […]

   Read more of: Using AI to track whales from space

   

6. PhD centre will nurture new leaders in Earth observation

   A new centre will enable 50 fully-funded PhD researchers to harness satellite data to tackle global environmental challenges. The Centre for Satellite Data in Environmental Science (SENSE) will bring together expertise in […]

   Read more of: PhD centre will nurture new leaders in Earth observation

   

7. Using AI to help tackle global environmental challenges

   A new Centre for Doctoral Training, involving researchers from British Antarctic Survey, will develop Artificial Intelligence (AI) techniques to address critical environmental challenges. Climate change and environmental hazards pose some […]

   Read more of: Using AI to help tackle global environmental challenges

   

8. Watching whales from space

   Scientists have used detailed high-resolution satellite images provided by Maxar Technologies’ DigitalGlobe, to detect, count and describe four different species of whales. Reported this week in the journal Marine Mammal […]

   Read more of: Watching whales from space

   

1. Seeing double: Digital twins and net zero

   Reaching net zero, as a country or a business, requires new measures, technology and innovations. Digital twins are an example of this; they can be a powerful tool to drive innovation and efficiency.

   Read more of: Seeing double: Digital twins and net zero

   

2. Predicting September 2021 Arctic sea ice using artificial intelligence

   Tom Andersson, a data scientist at British Antarctic Survey Artificial Intelligence (AI) Lab, shares the latest predictions from a new Arctic sea ice forecasting AI tool as this year’s Arctic […]

   Read more of: Predicting September 2021 Arctic sea ice using artificial intelligence

   

3. Innovative Research Sprints Tackle Challenges in Biodiversity and Exposure

   Over the last decade, digital technologies, including Artificial Intelligence, developed rapidly as did our capability to monitor our home planet from space with Earth Observation satellites. How can we most […]

   Read more of: Innovative Research Sprints Tackle Challenges in Biodiversity and Exposure

   

4. Earth Day 2020: A new age of Arctic science discovery – the AI way

   When we see news reports on climate change on our TV, they are often accompanied by footage of a polar bear walking over the icy Arctic landscape. But the Arctic […]

   Read more of: Earth Day 2020: A new age of Arctic science discovery – the AI way

   

5. Official launch of the BAS AI Lab!

   Today we officially launched the BAS AI Lab – thank you everyone for coming!

   Read more of: Official launch of the BAS AI Lab!

   

6. AI Lab presents at the First Artificial Intelligence for Copernicus Workshop

   Andrew Fleming and Anita Faul present their research at the First Artificial Intelligence for Copernicus Workshop  

   Read more of: AI Lab presents at the First Artificial Intelligence for Copernicus Workshop

   

7. Machine Learning for Environmental Sciences

   Rachel Furner is a PhD student at British Antarctic Survey, which has recently opened up its new AI Lab, that aims to foster the application of various machine learning (and […]

   Read more of: Machine Learning for Environmental Sciences

   

8. Data Study Group: Automated monitoring of seals via high-resolution satellite imagery

   Prem hosted at Data Study Group at the Alan Turing Institute Seals from space: automated Antarctic ecosystem monitoring via high-resolution satellite imagery Antarctic seal populations are potential indicators for the […]

   Read more of: Data Study Group: Automated monitoring of seals via high-resolution satellite imagery

   

9. Automated clustering of storm tracks for interpreting ice core records

   Accumulation in coastal West Antarctic ice core records and the role of cyclone activity Cyclones are an important component of Antarctic climate variability, yet quantifying their impact on the polar […]

   Read more of: Automated clustering of storm tracks for interpreting ice core records