Gregory Duveiller
Gregory Duveiller holds a PhD in agronomical science and biological engineering from the Université catholique of Louvain (UCLouvain), Belgium. After his PhD, he spent 10 years working at the European Commission Joint Research Centre (JRC), in Ispra, Italy. He has specialized in developing methods to combine different satellite remote sensing data streams to better monitor and understand land processes, including crop yield monitoring, land cover change and land-atmosphere interactions. Since 2021 he is a project group leader at the Max Planck Institute for Biogeochemistry in Jena, Germany. His main research aims at improving our understanding of the role of terrestrial ecosystems in the Earth System by using data-driven yet process-based thinking applied to satellite Earth Observation data. A key focus is on exploring the complexity and diversity of terrestrial ecosystems, and how their specific functional properties affect land-atmosphere interactions. Topics explored under this umbrella include: (i) improving estimations of carbon, water and energy fluxes; (ii) studying the role of biodiversity (specifically functional diversity) to improve ecosystem resilience; (iii) exploring the biophysical effects of land use and land management on climate.
Sessions
The Planetary Health Index (PHI) framework has been proposed as an innovative tool to summarize and analyze complex data about the state of the planet. The idea is to create an index composed of three separate interpretable axes, each representing one of the domain "spheres" of interest (atmosphere, biosphere and socio-economy). The resulting framework allows one to identify how one sphere affects another for a given region during a given time frame. The statistical method behind is a 3-way canonical correlation analysis (CCA). A first global prototype was demonstrated at global level combining yearly world bank data and the Earth System Data Cube (ESDL) gridded at quarter degree spatial resolution. However, this spatio-temporal configuration may be too coarse to properly characterize the complexity of global interlinkages between atmosphere, biosphere and socio-economy. We have thus ported the PHI framework to a finer spatio-temporal resolution by testing it at European level, leveraging on the daily 5km data cube of input and outputs of FLUXCOM-X-BASE along with EUROSTAT socio-economic data. We will present first results exploring whether we can use this framework to answer questions pertaining to implications of nature degradation on price inflation.