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DERI Seminar with Natalia Efremova, Leveraging AI and satellite imagery for sustainable agriculture 

When: Thursday, February 9, 2023, 11:00 AM - 12:00 PM
Where: Zoom

Speaker: Natalia Efremova, Lecturer in Digital Economy at QMUL

Zoom link: https://qmul-ac-uk.zoom.us/j/81148100921
Title: Leveraging AI and satellite imagery for sustainable agriculture 
Abstract: Corporations are facing growing pressure to decrease greenhouse emissions. For organisations, there are two ways to align with global climate strategies: cutting their own emissions and voluntary carbon offsetting. Voluntary carbon offsetting refers to paying another organisation for carbon removal on their behalf. This method is associated with several well-known risks, including improper carbon accounting, re-release of stored carbon and negative unintended consequences on humans and ecosystems. The above risks and their negative consequences can be accounted for if a system of regular monitoring of carbon offsets is in place. In the case of agroforestry solutions (e.g., reforestation or improvement of agricultural practices to store more carbon) and organic soil carbon, such monitoring is required over very large territories. This talk will discuss artificial intelligence (AI)- based methods, which, combined with satellite or aerial imagery, can provide long-term monitoring of carbon offsetting projects on a large scale. Specifically, we will discuss using AI methods for monitoring of above-ground biomass (AGB) and soil organic carbon (SOC) with ground-based instruments and satellite imagery.
Bio: Dr Natalia Efremova is a lecturer in Digital Economy in Queen Mary University, London. She has background in computer science. She had obtained her PhD in neural networks for brain modelling from the University of Kyoto, Japan and an MBA from the University of Oxford. Natalia’s research focuses on Machine Learning (ML) and primarily deep neural networks for pursuing sustainable goals. This includes defining the areas where ML tools would be especially advantageous within targets related to climate change, sustainable agriculture, water, and food scarcity, as well as monitoring progress towards market adoption of the new AI-based technologies for water-, agri- and waste- tech industries.

 

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