Leveraging the latest multimodal sensing technologies, IOT devices and the Microsoft Azure Cloud, the project will build artificial intelligence (AI) models that can inform more effective and sustainable management practices, leading to significant carbon reduction.
Data will be captured from satellites, airborne platforms, as well as in-field instruments, from 14 test sites strategically located across Ireland. To ensure a broad representation of land usage, and to improve our understanding of the interactions between the land and human activities that lead to carbon emissions, the test sites will include all types of land from grasslands, croplands, forestry, wetlands, peatlands, to urban areas.
Research in this area to date has focused on individual land use types, or activities relating to a specific sector. This project will integrate insights and data from multiple land types and multiple sectors into a modelling framework that will inform more effective policies to reduce carbon emissions. It will also help to inform future land use practices that will achieve reduced carbon outputs such as, precision farming, carbon sequestration of grassland, and new approaches to public transport, or even tree planting in urban areas.
While the project is capturing data from land types in Ireland, the intention is to design a cloud platform that can use the insights from the Irish findings and be shared with other countries to help them explore land usage and carbon reduction in their own jurisdictions.