Summary of the Final Report of Research Results1) Title of the proposed research
Space-based analysis of the relationship between vegetation functioning and atmospheric CO2
and CH4 greenhouse gases
2) Principal Investigator (PI) and Co-Investigators (Co-Is)
PI:
Dr. Luis Guanter
Co-I:
Dr. Luis Gómez-Chova
Dr. Jose Moreno
Dr. Roy Gordon Grainger
Dr. Anu Dudhia
3) PI’s affiliation
Freie Universitaet Berlin / GFZ Potsdam4) Summary of the Final Report of Research Results
The terrestrial sun-induced chlorophyll fluorescence signal (Fs) is emitted by the photosystem II of
the chlorophyll molecules of assimilating leaves: part of the energy absorbed by chlorophyll is not
used for carbon fixation, but re-emitted at longer wavelengths in the 650–800 nm spectral region(Papageorgiou,1975; Baker, 2008). The Fs signal originates at the cores of the photosynthetic
machinery and responds instantaneously to perturbations in the environmental conditions such as
light and water stress. This makes it a more direct proxy to the plant photosynthetic activity than thereflectance-based vegetation indices traditionally used in vegetation remote sensing applications(Coops et al., 2010). The very recent publication of the first global maps of chlorophyll fluorescence(Joiner et al., 2011; Frankenberg et al., 2011b) opens the door to a new, unexplored field of researchthat couples remote sensing with vegetation and atmospheric sciences.
The Fs retrieval methods developed by Joiner et al. (2011) and Frankenberg et al. (2011a,b) share acommon fundamental basis: the fractional depth of solar Fraunhofer lines decreases due to in-fillingby Fs. The feasibility of Fs retrieval using individual Fraunhofer lines had been proposed some yearsago (Sioris et al., 2003). However, it has not been until the advent of the Greenhouse gases
Observing SATellite ”IBUKI” (GOSAT), carrying the Thermal And Near infrared Sensor for carbon
Observation (TANSO) (Kuze et al., 2009), that the first global Fs maps have been produced. TANSO
includes a Fourier Transform Spectrometer (FTS) measuring with high spectral resolution in the755–775 nm range, which allows to resolve individual Fraunhofer lines overlapping the Fs emission.

This report corresponds to the research activity performed during the time period September 2011 toAugust 2015 for the GOSAT 2nd Research Announcement project entitled Space-based analysis of
the relationship between vegetation functioning and atmospheric CO2 and CH4 greenhouse gases.
As it is described in the document, this research has mostly dealt with the development of methods
for the retrieval of terrestrial chlorophyll fluorescence from TANSO-FTS measurements. On the one
hand, a data-driven method based on singular vector decomposition (SVD) has been developed(Guanter et al., 2012). This method is based on a statistical approach as opposed to thephysically-based approaches previously developed by Frankenberg et al. (2011a) and Joiner et al.
(2011). The main advantage of this method is that it has a linear forward model which can beinverted by non-weighted linear regression and that it does not require the modeling of theinstrument line shape function and external solar irradiance data sets. On the other hand, a new SIF
retrieval approach (GARLIC, for GOSAT Retrieval of chlorophyll fluorescence) is presented(Köhler et al., 2015). This method is intended to simplify some of the assumptions of existingretrieval approaches without a loss of accuracy. In addition, we have used existing GOSAT-based
SIF data derived with the approach described in Guanter et al (Guanter et al., 2012) as a reference
for an initial quality check of the recent SIF retrievals performed from MetOp-A GOME-2 data by
Joiner et al (Joiner et al., 2013).
The SVD-based retrieval method makes use of the Fraunhofer lines located in two spectral windowsof 2–3 nm centered in 755 and 770 nm to disentangle Fs from the solar radiation reflected by thesurface-atmosphere system. The inversion of TOA radiances is achieved by means of a linear
forward model consisting of a basis of orthogonal vectors to reproduce Fs-free spectral patterns plus
the fluorescence contribution. The basis of singular vectors has been derived with the singular vector
decomposition of a training set of vegetation-free spectra for the two spectral micro-windows.
Whereas this SVD-based method has some fundamental similarities with the state-of-the-art
approach described in Frankenberg et al. (2011a,b) (same two spectral micro-windows, twopolarizations processed separately, empirical correction of radiometric offsets), this method may
have some advantageous features such as a simple implementation and a higher efficiency.
Concerning the GARLiC full-physics retrieval method also developed in this project, it demonstrates
that simplifying some assumptions of the existing state-of-the-art algorithm by Frankenberg et al.
Frankenberg et al. (2011a) is not leading to a loss of accuracy in the retrieval. The simplifications
consist in neglecting the spectral stretch and decoupling the spectral shift estimation from theforward operator. Thus the GARLiC forward model is linear and easy to invert with the ordinary
least squares method.
In addition, we have demonstrated that SIF composites have a lower precision in presence of clouds
because of the lower number of available soundings, but the changes in accuracy for a wide range ofcloud coverage is only marginal. For this reason, it can be stated that the SIF retrieval is less affectedby clouds than reflectance-based vegetation indices. These finding impact future developments on
SIF retrieval for the upcoming OCO-2 system (Frankenberg et al. (2014)), which will have spectralcharacteristics similar to those of the GOSAT-FTS and will provide about 100 times moremeasurements than GOSAT.
This document provides a summary of the fundamentals of the retrieval methods by Guanter et al.
and Köhler et al. developed in this project as well as of the results found after the comparison withequivalent retrievals with other methods and with state-of-art vegetation products based on remotesensing data, including fluorescence retrievals from GOME-2 by Joiner et al.
5) List of publications relating to the proposed research
1. Guanter, L., C. Frankenberg, A. Dudhia, P. E. Lewis, J. Gómez-Dans, A. Kuze, H. Suto, andR. G. Grainger (2012), Retrieval and global assessment of terrestrial chlorophyll fluorescence fromGOSAT space measurements, Remote Sensing of Environment, 121, 236–251.
2. Joiner, J., L. Guanter, R. Lindstrot, M. Voigt, A. P. Vasilkov, E. M. Middleton, K. F. Huemmrich,
Y. Yoshida, and C. Frankenberg (2013), Global monitoring of terrestrial chlorophyll fluorescencefrom moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations,and application to GOME-2, Atmospheric Measurement Techniques, 6(10), 2803–2823.
3. Guanter, L., et al. (2014), Global and time-resolved monitoring of crop photosynthesis withchlorophyll fluorescence, Proceedings of the National Academy of Sciences, 111(14), E1327–E1333.
4. Köhler, P., L. Guanter, and C. Frankenberg (2015a), Simplified physically based retrieval of
sun-induced chlorophyll fluorescence from GOSAT data, Geoscience and Remote Sensing Letters,IEEE, 12(7), 1446–1450.
5. Köhler, P., L. Guanter, and J. Joiner (2015b), A linear method for the retrieval of sun-induced
chlorophyll fluorescence from GOME-2 and SCIAMACHY data, Atmospheric Measurement
Techniques, 8(6), 2589–2608.