PhotoProxy: Technical Assistance for the Photosynthetic-Proxy Experiment

In few years from now, ESA’s BIOMASS and FLEX Earth Explorers satellite missions will open a new opportunity to enhance our knowledge of the global carbon cycle. In particular, the scientific exploitation of BIOMASS and FLEX in synergy with the Sentinel satellite series and other existing and future missions (e.g. CMOS, GEDI, NISAR, Tandem-X/L) will provide an unprecedented opportunity to better understand and characterize the different components of the carbon cycle and its dynamics. Preparing for the fast exploitation of this unique and unprecedented observational capacity, ESA has launched the Carbon Science Constellation Initiative. This initiative will be implemented through a cluster of different studies, research activities, campaigns and tool development efforts dedicated to support the scientific community to explore the potential synergies between different Earth Observation approaches and maximize the scientific impact of this unique set of sensors for carbon cycle research.

With the PhotoProxy project, we address relevant open aspects that are related to the quantitative assessment of vegetation photosynthesis and vegetation stress from space. In the past years the fluorescence signal that is emitted from the core of the photosynthetic apparatus during photosynthetic energy conversion, has become the most promising indicator of actual photosynthetic rates. In 2012, the European Space Agency has selected the FLEX satellite mission to become ESA’s 8th Earth Explorer mission (Drusch et al. 2017). FLEX will be the first dedicated fluorescence mission that will provide global maps of both peak of the fluorescence signal on a high spatial resolution and relevant revisiting time.

In addition to fluorescence, which can be measured across various scales ranging from the single leaf to the ecosystem (Rascher et al 2015, Wieneke et al 2018), in recent years, alternative approaches to the remote detection of photosynthetic carbon fluxes (photosynthesis or gross primary productivity, GPP) have been proposed. These approaches include reflectance-based measures by NIRv (Badgely et al. 2017) and CCI (Gamon et al. 2016), which are both related to pigment and structurally-based changes in vegetation [see Fig below as an example for the complementary information content of the different remote sensing measures]

Copyright: Forschungszentrum Jülich, IBG-2

Projekt Photoproxy (ESA: Project number RFP No. 3-15506/18/NL/LF,
ESA contract NO. 4000125731/19/NL/LF)

A map section of the agricultural region around Jülich (Germany) near Selhausen with an Eddy station and FloxBox on the ground (red circle, left map). The map sections are processed from high resolution imaging spectrometer HyPlant (Rascher U. et al. 2015) and show from left to right: true color image, Sun-induced fluorescence retrieved by iFLD method at 760 nm and F687 nm, CCI index and NIRv index (calculated by NDVI*reflection at 800 nm). Within the PhotoProxy project imaging data and time series of ground based spectrometers and eddy stations will be analysed for a better understanding of the link between reflectance based remote sensing measures, sun-induced-fluorescence and vegetation carbon uptake.

Together, these remote sensing approaches offer a way to revolutionize our assessment of photosynthetic carbon uptake and vegetation health from space. However, major questions remain regarding the exact function of each of these signals and their relationship to each other. There are several indications that fluorescence may be the best remote sensing parameter to constrain predictions of CO₂ uptake rates, but we expect that a combination of the different measures will provide the best estimates of actual vegetation function.
Thus with this activity we are working in an international consortium to address the following objectives:

1. Test the applicability of the recently developed reflectance indices CCI and NIRv to track diurnal and seasonal vegetation dynamics.
2. Perform a comparison of CCI, NIRv and solar induced chlorophyll fluorescence to better judge the quality of the different approaches to understand and model vegetation dynamic.
3. Compare a benchmark dataset of those parameters to flux estimates from airborne and ground-based systems.
4. Determine the scale-dependence (temporal and spatial) of the correlation between each optical metric and photosynthetic carbon uptake.
5. Determine the factors that confound the interpretation of reflectance-based signals, and the conditions under which these occur.
6. Determine the degree by which physiological regulation and structural adjustments influence each signal.
   

Cooperating partners

University of Lincoln Nebrasca

https://www.unl.edu/

University of Alberta

https://www.ualberta.ca/

Carnegie Institution of Gloabal Ecology
https://carnegiescience.edu/scientist/joseph-berry

Max Planck Institute of Bio-Geochemsitry
https://www.bgc-jena.mpg.de/bgi/index.php/People/MircoMigliavacca

MetAir AG
https://www.metair.ch/index.php/de/

University of Bonn
https://www.uni-bonn.de/startpage?set_language=en

Wageningen University
https://www.wur.nl/en/wageningen-university.htm

Fondazione Clima e Sostenibilitá
http://www.climaesostenibilita.it/

Technicalassistance for the photosynthetic-proxyexperiment

https://eo4society.esa.int/projects/photoproxy-technical-assistance-for-the-photosynthetic-proxy-experiment

Related publications

Badgley G, Field C.B. and Berry J.A. (2017) Canopy near-infrared reflectance and terrestrial photosynthesis. Science Advances, 3; e1602244

Drusch M., Moreno J., Del Bello U., Franco R., Goulas Y., Huth A., Kraft S., Middleton E., Miglietta F., Mohammed G., Nedbal L., Rascher U., Schüttemeyer D. & Verhoef W. (2017) The FLuorescence EXplorer mission concept - ESA’s Earth Explorer 8. IEEE Transactions on Geoscience and Remote Sensing, 55, 1273-1284

Gamon J.A., Huemmrich K.F., Wong C.Y.S, Ensminger I., Garrity S., Hollinger D.Y., Noormets A., Peñuelas J. (2016) Photosynthetic phenology of evergreen conifers. Proceedings of the National Academy of Sciences, 113 (46), 13087-13092

Rascher U., Alonso L., Burkart A., Cilia C., Cogliati S., Colombo R., Damm A., Drusch M., Guanter L., Hanus J., Hyvärinen T., Julitta T., Jussila J., Kataja K., Kokkalis P., Kraft S., Kraska T., Matveeva M., Moreno J., Muller O., Panigada C., Pikl M., Pinto F., Prey L., Pude R., Rossini M., Schickling A., Schurr U., Schüttemeyer D., Verrelst J. & Zemek F. (2015) Sun-induced fluorescence - a new probe of photosynthesis: First maps from the imaging spectrometer HyPlant. Global Change Biology, 21, 4673–4684

Wieneke S., Burkart, A., Cendrero-Mateo M. P., Julitta T., Rossini M., Schickling A., Schmidt M., Rascher U. (2018) Linking photosynthesis and sun-induced fluorescence at sub-daily to seasonal scales. Remote sensing of environment, 219, 247 – 258

Results from this project

Wang R., Gamon J.A., Emmerton C.A., Springer K.R., Yu R. & Hmimina G. (2020). Detecting intra-and inter-annual variability in gross primary productivity of a North American grassland using MODIS MAIAC data. Agricultural and Forest Meteorology, 281, 107859. 

Vilá-Guerau de Arellano J., Ney P., Hartogensis O., de Boer H., van Diepen K., Emin D., de Groot G., Klosterhalfen A., Langensiepen M., Matveeva M., Miranda G., Moene A., Rascher U., Röckmann T., Adnew G., Graf A., Brüggemann N., Rothfuss Y., Graf A. (2020). CloudRoots: Integration of advanced instrumental techniques and process modelling of sub-hourly and sub-kilometre land-atmosphere interactions. Biogeosciences, 17, 4375-4404, https://doi.org/10.5194/bg-17-4375-2020

Martini D., Pacheco-Labrador J., Perez-Priego O., van der Tol C., El-Madany T. S., Julitta T., Rossini M., Reichstein M., Christiansen R., Rascher U., Moreno G., Pilar Martin M., Yang P., Carrrara A., Guan J., Gonzalez-Cascon R., Migliavacca M. (2019). Nitrogen and Phosphorus Effect on Sun-Induced Fluorescence and Gross Primary Productivity in Mediterranean Grassland. remote sensing, 11, 2562 https://doi.org/10.3390/rs11212562

Martini D., Pacheco Labrador J., El-Madany T.S., Sakowska K., van der Tol C., Julitta T., Biriukova K., Rossini M. & Migliavacca M. (2019). Sun-Induced Fluorescence under a heat wave. Evidence from a tree-grass ecosystem. AGU Fall Meeting 2019, San Francisco: B11Q-2282

Quirós J., Brogi C., Krieger V., Siegmann B., Celesti M., Rossini M., Cogliati S., Weihermüller L., Rascher U. (2020). Solar Induced Chlorophyll Fluorescence and Vegetation Indices for Heat Stress Assessment in Three Crops at Different Geophysics-Derived Soil Units. AGU Fall Meeting 2020, Virtual, doi: 10.1002/essoar.10504968.1

Ran Wang, John A. Gamon, Ryan Moore, Arthur I. Zygielbaum, Timothy J. Arkebauer, Rick Perk, Bryan Leavitt, Sergio Cogliati, Brian Wardlow, Yi Qi (2021). Errors associated with atmospheric correction methods for airborne imaging spectroscopy: Implications for vegetation indices and plant traits, Remote Sensing of Environment, Volume 265, 112663,https://doi.org/10.1016/j.rse.2021.112663.

Zeng Y, Hao D., Badgley G., Damm A., Rascher U., Ryu Y., Johnson J., Krieger V., Wu S., Qiu H., Liu Y., Berry J.A. & Chen M. (2021). Estimating near-infrared reflectance of vegetation from hyperspectral data. Remote Sensing of Environment, 267, article no. 112723, https://doi.org/10.1016/j.rse.2021.112723

Siegmann B., Pilar Cendrero-Mateo M., Cogliati S., Damm A., Gamon J., Herrera D., JedmowskiC., Junker-Frohn L. V., Kraska T., Muller O., Rademske P, van der Tol C., Quiros-Vargas J., Yang P., RascherU. (2021). Downscaling of far-red solar-induced chlorophyll fluorescence of different crops from canopy to leaf level using a diurnal data set acquired by the airborne imaging spectrometer HyPlant. Remote Sensing of Environment, 264, 112609. https://doi.org/10.1016/j.rse.2021.112609

Yelu Zeng, Min Chen, Dalei Hao, Alexander Damm, Grayson Badgley, Uwe Rascher, Jennifer E. Johnson, Benjamin Dechant, Bastian Siegmann, Youngryel Ryu, Han Qiu, Vera Krieger, Cinzia Panigada, Marco Celesti, Franco Miglietta, Xi Yang, Joseph A. Berry (2022) Combining near-infrared radiance of vegetation and fluorescence spectroscopy to detect effects of abiotic changes and stresses, Remote Sensing of Environment, Volume 270,112856, ISSN 0034-4257.

Contacts IBG-2

Prof. Dr. Uwe Rascher