Modeling CO2 sequestration through remote sensing and artificial intelligence
Carbon dioxide (CO2) levels in the atmosphere have risen to historic levels, compared to the pre-industrial era, which is usually taken as a standard measure. These levels of CO2 are due to emissions from human activity, and are the main cause of the effects of climate change such as rising temperatures and acidification of the oceans. Although fossil fuels are the primary source of anthropogenic emissions, land use change (LUC) has historically been the main component of human emissions. It still accounts for about 12% of these. The main reason for the change in land use is the demand created mainly by agriculture and deforestation. Climate action in this direction is therefore urgently needed to reverse the effects of deforestation and harness the potential of trees as CO2 sequestrants. The lack of large databases for modeling and understanding this global CO2 sequestration is necessary for the correct decision-making and sustainability of related projects. Remote sensing monitoring has the potential to generate a large amount of data that can be used for this purpose. In this context, Lobelia Offset will develop and implement a remote sensing monitoring system for the calculation of carbon dioxide uptake in forested and reforested areas. This calculation will be used to trigger a system of payments for environmental services (PES) of reforestation and assisted natural regeneration and will serve as CO2 offsetting, also known as CO2 offsetting. This system will be based on observations of different types of satellites and artificial intelligence models. It will be implemented in tropical areas of the African continent and will be validated with in-situ databases and existing LiDAR satellite products.
Researcher: Martí Perpinyà
Supervisor: Maria Jose Escorihuela
Co-supervisor: Aitor Ameztegui