Research projects

FLORES is unlocking the hidden life of forests. Using cutting-edge measurements of sun-induced chlorophyll fluorescence (SIF) from drones to satellites, it measures forest photosynthesis and water use in real time. This allows early detection of stress and improves estimates of carbon uptake, helping Europe’s forests thrive in a changing climate.

This project aims to advance Critical Zone research by uncovering the hydrological controls on carbon and nutrient fluxes. By integrating proximal sensing, field measurements, and smart modeling, it offers deeper insights into ecosystem dynamics and biogeochemical cycles.

This project aims to investigate the role of hydrological changes resulting from permafrost thaw on carbon and nutrient fluxes using very-high resolution remote sensing and geochemical techniques. It focuses on understanding the spatial and temporal effects of permafrost degradation on soil hydrology and dissolved organic carbon (DOC) concentrations. The findings will enhance our understanding of permafrost carbon emissions, critical for assessing whether these ecosystems act as long-term carbon sinks or sources.

This project aims to predict wildfire risk in European forest ecosystems by integrating Copernicus satellite data, in situ measurements, and vegetation modeling. By incorporating tree water status as a key input, it will generate high-resolution wildfire risk maps to support proactive forest management and climate adaptation strategies.

This project aims to study and predict the response of forest ecosystems to climate change and extreme events. The project combines climate modelling, vegetation modelling, and remote sensing through model coupling and data assimilation.

This research leverages UAV LiDAR and AI to detect individual trees, estimate key attributes (e.g., height, dbh, biomass), and classify species by integrating 3D and spectral data. By enhancing forest monitoring techniques, it contributes to more effective and sustainable forest management.