MSc thesis topic: Integrating PRISMA hyperspectral imagery with Sentinel-2 time series for estimating GPP using Biophysical models  and eddy covariance flux tower in European forest ecosystems.

The study will also explore methods for scaling PRISMA hyperspectral data to the Sentinel-2 time series at 20-meter resolution, focusing on spectral band selection to accurately capture biodiversity indicators. By utilizing RTM tools, the research will enhance forest health monitoring and improve our understanding of ecosystem dynamics, contributing to better climate change mitigation strategies..

Background

The ICOS network manages eddy covariance flux towers distributed across Europe that provides standardized data for measuring key ecosystem parameters such as Gross Primary Productivity (GPP) and carbon fluxes in various land ecosystems. In this study, EC flux towers in European forests will be used to validate remote sensing (RS) methods. This research infrastructure servers as critical monitoring points for understanding ecosystem dynamics and their role in carbon cycling.

To complement EC flux tower data, we use time-series data from Sentinel-2 and PRISMA satellites to monitor vegetation health, stress, and canopy structure over time. Additionally, we use RTM simulations with the ToolsRTM package to retrieve functional plant traits like leaf area index, chlorophyll content, and photosynthesis rates. These estimates will be validated with data from ICOS sites to ensure accuracy. By integrating satellite data from multiple ICOS flux tower sites across evergreen, deciduous and mixed European forests, we aim to improve our understanding of how forest ecosystems respond to environmental changes and their contribution to carbon cycling.

Relevance to research/projects at GRS or other groups

This research is a collaboration between the Consiglio Nazionale delle Ricerche (CNR) and the Geo-Information Science and Remote Sensing (GRS) group. Dr. Carlos Camino from GRS and Dr. José Luis Pancorbo, from CNR in Florence, lead the project. It integrates remote sensing and ecosystem flux data to enhance the retrieval of functional plant traits and improve ecosystem modeling.

Objectives and Research questions

The objective of this thesis is to develop a comprehensive ecosystem monitoring framework by integrating PRISMA hyperspectral data, ICOS Flux Towers measurements, and radiative transfer models (RTM) to estimate Gross Primary Productivity (GPP) and other functional traits in forest ecosystems. Key research questions include:

• How can PRISMA hyperspectral data be scaled to Sentinel-2’s resolution for reliable biodiversity monitoring?
• What are the key functional traits that influence GPP estimation using RTM models?
• How can the integration of ICOS Flux Towers measurements improve ecosystem function models?

Requirements

• Required: Geoscripting, Machine Learning, Remote Sensing, Advance Earth Observation
• Optional: Spatial Modelling and Statistics, Deep Learning

Literature and information

• Kooistra, L., Berger, K., Brede, B., Graf, L. V, Aasen, H., Roujean, J.-L., Machwitz, M., Schlerf, M., Atzberger, C., Prikaziuk, E., Ganeva, D., Tomelleri, E., Croft, H., Reyes Muñoz, P., Garcia Millan, V., Darvishzadeh, R., Koren, G., Herrmann, I., Rozenstein, O., … Verrelst, J. (2024). Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity. Biogeosciences, 21(2), 473–511.
• Baldocchi, D. D. (2020). How eddy covariance flux measurements have contributed to our understanding of Global Change Biology. Global Change Biology, 26(1), 242–260.
• Verrelst, J., Rivera, J. P., Leonenko, G., Alonso, L., & Moreno, J. (2014). Optimizing LUT-based RTM inversion for semiautomatic mapping of crop biophysical parameters from sentinel-2 and -3 data: Role of cost functions. IEEE Transactions on Geoscience and Remote Sensing, 52(1), 257–269.

Expected reading list before starting the thesis research

• Cogliati, S., Sarti, F., Chiarantini, L., Cosi, M., Lorusso, R., Lopinto, E., Miglietta, F., Genesio, L., Guanter, L., Damm, A., Pérez-López, S., Scheffler, D., Tagliabue, G., Panigada, C., Rascher, U., Dowling, T. P. F., Giardino, C., & Colombo, R. (2021). The PRISMA imaging spectroscopy mission: overview and first performance analysis. Remote Sensing of Environment, 262. (Pabon-Moreno et al., 2022)
• Pabon-Moreno, D. E., Migliavacca, M., Reichstein, M., & Mahecha, M. D. (2022). On the Potential of Sentinel-2 for Estimating Gross Primary Production. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–12.

Theme(s): Modelling & visualisation; Integrated Land Monitoring