|UK Students, EU Students, International Students
|Full Time, Part Time
|28th November 2023
|29th February 2024
It is an exciting interdisciplinary research opportunity to develop innovative AI and machine learning approaches aimed at addressing global warming and greenhouse gas (GHG) emissions. By leveraging multimodal big data from satellites, remote sensing, and ground-based scientific measurements, this project will explore AI-enhanced solutions to improve GHG emission monitoring and analysis. It will also investigate the association between land use (e.g., agriculture, industry) and biodiversity concerning climate change and GHG emissions. The project will contribute to the UKRI/EPSRC £2.5M project on AI for sustainable land management (https://www.lboro.ac.uk/media-centre/press-releases/2023/june/ai-twin-big-data-show-way-to-net-zero).
Greenhouse gas emissions and land use play crucial roles in shaping the trajectory of climate change, with far-reaching impacts on both the environment and human societies. The rise in GHG poses severe threats to humans, ecosystems, and biodiversity.
Actions to reduce GHG emissions are urgent, and require accurate and complete data to guide informed decision-making and innovation. Satellite, remote sensing, and ground-based GHG measurements provide useful ways. Satellites offer a comprehensive view of the Earth's surface, allowing for global coverage, real-time and consistent monitoring, but suffer from resolution limitations and sensitivity to cloud cover. Remote sensing (e.g., airborne sensors or drones) and ground-based stations offer better precision in GHG concentrations but require intensive resources for extensive monitoring.
The developed AI technology will focus on: 1) Multimodal data fusion and integration to address the limitations of individual measurement approaches, 2) Pattern recognition and anomaly detection, 3) Spatial-temporal analysis and predictive models, 4) Understanding the association between GHG emissions and land use, enabling the identification of the origins of emissions to effectively target mitigation efforts.
The Department of Computer Science has an excellent research record in AI, machine learning, robotics, computer vision and data science. The successful candidate will have access to robotics and AI laboratories, high-spec computing facilities (e.g., GPUs), HPC, and £5.8M DigLabs, complementing a £9m investment in research and teaching. You will have regular supervision meetings and work with a strong AI research team (over 30 PhDs/PDRAs/academic staff) at Loughborough and be supported by environmental scientists at the National Centre for Earth Observation.
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