Earth Observation and deep learning: towards biodiversity enhancing, low carbon farming and land-use systems Theme(s): Artificial Intelligence, Crops, Vegetation Primary Supervisor: Dr Nabi Omidvar <M.N.Omidvar@leeds.ac.uk> Institution: University of Leeds (School of Computing)
Combining AI and remote sensing to understand how climate change will affect the second largest rainforest on Earth Theme(s): Artificial Intelligence, Climate, Ecosystem processes, dynamics and functioning, Forest Primary Supervisor: Dr David Williams <d.r.williams@leeds.ac.uk> Institution: University of Leeds (School of Earth and Environment)
Measuring the climate-smart practices using crop modelling, machine learning and remote sensing Theme(s): Artificial Intelligence, Climate, Crops, Earth Observation Primary Supervisor: Professor Andy Challinor Institution: University of Leeds (School of Earth and Environment)
Discovering the dynamics of cloud development through the embedding space of a self-supervised neural network Theme(s): Artificial Intelligence, Atmosphere and Climate, Earth Observation Primary Supervisor: Dr Leif Denby <l.c.denby@leeds.ac.uk> Institution: University of Leeds (School of Earth and Environment)
Greenland Ice Sheet – Ocean Interactions: Using satellite data and AI to understand ice dynamic change Theme(s): Artificial Intelligence, Climate, Cryosphere, Earth Observation, Glaciology, RADAR, Sea Ice Primary Supervisor: Dr Anna Hogg <A.E.Hogg@leeds.ac.uk> Institution: University of Leeds (School of Earth and Environment)
Deriving pressure fields in Antarctic sea ice from satellite observations Theme(s): Artificial Intelligence, Earth Observation, Machine Learning, RADAR, Sea Ice Primary Supervisor: Dr Martin Rogers <marrog@bas.ac.uk> Institution: British Antarctic Survey
A new, automated, high-resolution global wetland change map Theme(s): Artificial Intelligence, Climate, Earth Observation, ecosysetms, water Primary Supervisor: Prof Joseph Holden <J.Holden@leeds.ac.uk> Institution: University of Leeds (School of Geography)
Can air-sea coupling solve the signal-to-noise paradox in climate predictions? Theme(s): Artificial Intelligence, Atmosphere and Climate, Climate, Machine Learning, ocean Primary Supervisor: Dr Amanda Maycock <A.C.Maycock@leeds.ac.uk> Institution: University of Leeds (School of Earth and Environment)
Data-driven measuring, modelling and predicting the hole in the Earth’s magnetic field Theme(s): Artificial Intelligence, Atmospheric Physics, Geomagnetic Field, Machine Learning, Satellite Data Primary Supervisor: Professor Phil Livermore <p.w.livermore@leeds.ac.uk> Institution: University of Leeds (School of Earth and Environment)
Rapid damage assessment for earthquakes from synthetic aperture radar and machine learning Theme(s): Artificial Intelligence, Earth Observation, Earthquakes, Tectonics Primary Supervisor: Professor Tim Wright <t.j.wright@leeds.ac.uk> Institution: University of Leeds (School of Earth and Environment)
