Project Details
Description
Forests are important for both absorbing CO2 and creating oxygen. The overall carbon absorption - emission cycle however remains a puzzle. Forests, wetlands and general land use comprise critical pieces of that puzzle which are still not well understood. With wetlands holding some of the largest stores of carbon on the planet, their fate becomes a critical factor in predicting evolution of greenhouse gases, such as CO2 and methane, in our atmosphere. The main objective of the project is to develop mathematical tools linked to machine learning methods which enable monitoring and forecasting of carbon emissions/absorption from forestry management and wetland maintenance practices.
Short title | eSSENCE@LU 10:3 |
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Status | Active |
Effective start/end date | 2024/01/01 → 2025/12/31 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):