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Can we improve vegetation dynamics monitoring through hyperspectral remote sensing? Can Radiative Transfer Models bridge the observational gap between multi-scale, multi-source remote sensing data?

Marco Celesti


After a BSc in Natural Sciences at the University of Perugia with a thesis on the ecology of small carnivores and a MSc in Environmental Sciences at the University of Milano-Bicocca (UNIMIB) with a thesis on forest monitoring through multi-source remote sensing observations, Marco received a Ph.D. in Environmental Sciences at UNIMIB. His thesis focused on using multi-source remote sensing data to improve vegetation status analysis from above. In particular, he focused on using Sun-induced fluorescence, and fluorescence derived metrics, together with hyperspectral reflectance in the Visible and Near InfraRed (VNIR) spectral region, as tools for monitoring variations in the photosynthetic efficiency of plants in different conditions. During the Ph.D. Marco took part to several ESA-funded projects and field campaigns, mainly within the context of the future ESA Earth Explorer 8 FLEX mission. He also spent two months as a visiting scientist at the University of Twente, working with Dr. Ir. Christiaan van der Tol on a coupled inversion strategy for retrieving at the same time fluorescence and classical vegetation parameters from very high resolution hyperspectral measurements. Following the Ph.D., he worked for one year as a postdoc at UNIMIB, being also involved as project manager in the H2020 Marie Curie ITN TRUSTEE project. Currently, Marco is based at UNIMIB for a two year postdoc co-funded by the ESA Living Planet Fellowship programme, and is spending six months at ESA-ESTEC in Noordwijk (NL) working on Sentinel-3B OLCI data acquired in FLEX-like mode.

Research objectives

The main objective of the MULTI-FLEX project is to build and test flexible tools for assessing vegetation dynamics using multi-source, multi-resolution remote sensing data. The specific objectives of the project are:

  • to develop a processing chain for coupled retrieval of fluorescence and vegetation parameters from continuous ground hyperspectral measurements in FLEX-like spectral configuration;
  • to adapt and test this inversion scheme to the spectral resolution of the reconfigured Sentinel-3B OLCI;
  • to exploit HyPlant and Sentinel-3A top-of-canopy (TOC) products to test simple fluorescence-derived metrics such as CCFI and Fy at 300m x 300m spatial resolution;
  • to compare these fluorescence-derived metrics to reflectance-based indices linked to the vegetation functioning such as the NIRv, CCI and PRI;
  • to scale the inversion scheme proposed above to the reconfigured OLCI-B TOC data, and compute CCFI and Fy directly on satellite fluorescence observations at 300m x 300m spatial resolution.


  • Celesti, M., van der Tol, C., Cogliati, S., Panigada, C., Yang, P., Pinto, F., Rascher, U., Miglietta, F., Colombo, R., Rossini, M. (2018). Exploring the physiological information of Sun-induced chlorophyll fluorescence through radiative transfer model inversion. Remote Sensing of Environment, 215, 97–108.
  • Colombo, R., Celesti, M., Bianchi, R., Campbell, P. K. E., Cogliati, S., Cook, B. D., … Schickling, A. (2018). Variability of sun-induced chlorophyll fluorescence according to stand age-related processes in a managed loblolly pine forest. Global Change Biology, 24(7), 2980–2996.
  • Rossini, M., Meroni, M., Celesti, M., Cogliati, S., Julitta, T., Panigada, C., … Colombo, R. (2016). Analysis of red and far-red sun-induced chlorophyll fluorescence and their ratio in different canopies based on observed and modeled data. Remote Sensing, 8(5), 412.


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