Exploring continuous time series of vegetation hyperspectral reflectance and solar-induced fluorescence through radiative transfer model inversion
- 1University of Milano-Bicocca, Department of Earth and Environmental Sciences, Italy (marco.celesti@unimib.it)
- 2University of Maryland Baltimore County, JCET, Baltimore, MD, United States
- 3NASA Goddard Space Flight Center, Greenbelt, MD, United States
- 4EAWAG Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland
- 5University of Zurich, Zurich, Switzerland
- 6ESA-ESTEC, European Space Research and Technology Centre, Noordwijk, Netherlands
- 7JB Hyperspectral Devices, Dusseldorf, Germany
- 8Max-Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, Jena, Germany
- 9Istituto di Biometeorologia IBIMET-CNR, Firenze, Italy
- 10Forschungszentrum Jülich, Jülich, Germany
- 11University of Twente, ITC-Faculty of Geo-Information Science and Earth Observation, Enschede, Netherlands
- 12University of Valencia, Valencia, Spain
Remote sensing of solar-induced chlorophyll fluorescence (SIF) is of growing interest for the scientific community due to the inherent link of SIF with vegetation photosynthetic activity. An increasing number of in situ and airborne fluorescence spectrometers has been deployed worldwide to advance the understanding and usage of SIF for ecosystem studies. Particularly, a number of sites has been instrumented with the FloX (J&B Hyperspectral Devices, Germany), an automated instrument that houses two high resolution spectrometers covering the visible and near infrared spectral regions, one specifically optimized for fluorescence retrieval, the other for plant trait estimation.
In this contribution we explore the feasibility to consistently retrieve plant traits and SIF from canopy level FloX measurements through the numerical inversion of a light version of the SCOPE model. The optimization approach was specifically adapted to work with the high- frequency time series produced by the FloX. In this context, a strategy for optimal retrieval of plant traits at daily scale is discussed, together with the implementation of an emulator of the radiative transfer model in the retrieval scheme. The retrieval strategy was applied to site measurements across Europe and the US that span a variety of natural and agricultural ecosystems.
The full spectrum of canopy SIF, the fluorescence quantum efficiency, and main plant traits controlling light absorption and reabsorption were retrieved concurrently and evaluated over the growing season in comparison with site-specific ancillary data. Improvements and challenges of this method compared to other retrievals are discussed, together with the potential of applying a similar retrieval scheme to airborne datasets acquired with e.g. the HyPlant sensor, or the reconfigured “FLEX mode” data acquired with the recently launched Sentinel-3B during its commissioning phase.
How to cite: Celesti, M., Biriukova, K., Campbell, P. K. E., Cesana, I., Cogliati, S., Damm, A., Drusch, M., Julitta, T., Middleton, E., Migliavacca, M., Miglietta, F., Panigada, C., Rascher, U., Rossini, M., Schuettemeyer, D., Tagliabue, G., van der Tol, C., Verrelst, J., Yang, P., and Colombo, R.: Exploring continuous time series of vegetation hyperspectral reflectance and solar-induced fluorescence through radiative transfer model inversion, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14904, https://doi.org/10.5194/egusphere-egu2020-14904, 2020.
