A Caltech Library Service

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

Guanter, Luis and Zhang, Yongguang and Jung, Martin and Joiner, Joanna and Voigt, Maximillian and Berry, Joseph A. and Frankenberg, Christian and Huete, Alfredo R. and Zarco-Tejada, Pablo and Lee, Jung-Eun and Moran, M. Susan and Ponce-Campos, Guillermo and Beer, Christian and Camps-Valls, Gustavo and Buchmann, Nina and Gianelle, Damiano and Klumpp, Katja and Cescatti, Alessandro and Baker, John M. and Griffis, Timothy J. (2014) Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proceedings of the National Academy of Sciences of the United States of America, 111 (14). E1327-E1333. ISSN 0027-8424. PMCID PMC3986187. doi:10.1073/pnas.1320008111.

[img] PDF - Published Version
See Usage Policy.

[img] PDF - Supplemental Material
See Usage Policy.


Use this Persistent URL to link to this item:


Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50–75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.

Item Type:Article
Related URLs:
URLURL TypeDescription CentralArticle Information
Guanter, Luis0000-0002-8389-5764
Zhang, Yongguang0000-0001-8286-300X
Jung, Martin0000-0002-7569-1390
Joiner, Joanna0000-0003-4278-1020
Berry, Joseph A.0000-0002-5849-6438
Frankenberg, Christian0000-0002-0546-5857
Huete, Alfredo R.0000-0003-2809-2376
Zarco-Tejada, Pablo0000-0003-1433-6165
Ponce-Campos, Guillermo0000-0003-4332-338X
Beer, Christian0000-0002-5377-3344
Camps-Valls, Gustavo0000-0003-1683-2138
Buchmann, Nina0000-0003-0826-2980
Gianelle, Damiano0000-0001-7697-5793
Klumpp, Katja0000-0002-4799-5231
Baker, John M.0000-0002-7937-9839
Griffis, Timothy J.0000-0002-2111-5144
Additional Information:© 2014 National Academy of Sciences. Edited by Gregory P. Asner, Carnegie Institution for Science, Stanford, CA, and approved February 25, 2014 (received for review October 24, 2013) Published online before print March 25, 2014, doi: 10.1073/pnas.1320008111 We thank T. Meyers (National Oceanic and Atmospheric Administration Air Resources Laboratory), D. Cook and R. Matamala (Argonne National Laboratory), A. Suyker (University of Nebraska), C. Bernhofer (Technische Universität Dresden), Z. Nagy (Szent István University), M. Aubinet (Université de Liège), W. Kutsch (Johann Heinrich von Thuenen Institut), and K. Schneider (University of Cologne) for kindly providing eddy covariance data. We acknowledge C. Monfreda (Arizona State University), P. H. Verburg (Vrije Universiteit University Amsterdam), and N. Ramankutty (McGill University) for the crop fraction and NPP data sets and/or advice on their use, Eumetsat for the GOME-2 data, the Trendy project for the process-based model runs, and the USDA NASS for their agricultural inventory data. We also thank the two anonymous reviewers and Dr. Asner for their valuable suggestions and comments. MODIS MOD17 GPP data were downloaded from the server of the Numerical Terradynamic Simulation Group at the University of Montana, MODIS MOD13 data were obtained from the MODIS Land Processes Distributed Active Archive Center archive, and MERIS-MTCI from the Infoterra Ltd server. This work used eddy covariance data acquired by AmeriFlux and GHG-Europe. The work by L.G., Y.Z., and M.V. has been funded by the Emmy Noether Programme (GlobFluo project) of the German Research Foundation. J.J. is supported by the National Aeronautics and Space Administration (NASA) Carbon Cycle Science program (NNH10DA001N) and G.P.-C. is supported by NASA Soil Moisture Active Passive Science Definition Team (08-SMAPSDT08-0042). We also thank the W. M. Keck Foundation for funding the New Methods to Measure Photosynthesis from Space workshop held at the Caltech Keck Institute for Space Studies. L.G. and Y.Z. contributed equally to this work. Author contributions: L.G., Y.Z., M.J., and J.A.B. designed research; L.G., Y.Z., M.V., A.R.H., P.Z.-T., J.-E.L., M.S.M., and G.P.-C. performed research; L.G., Y.Z., M.J., J.J., C.B., G.C.-V., N.B., D.G., K.K., A.C., J.M.B., and T.J.G. contributed new reagents/analytic tools; L.G., Y.Z., J.J., M.V., and C.F. analyzed data; and L.G., Y.Z., J.A.B., C.F., and A.R.H. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. This article contains supporting information online at
Group:Keck Institute for Space Studies
Funding AgencyGrant Number
Deutsche Forschungsgemeinschaft (DFG)UNSPECIFIED
W. M. Keck FoundationUNSPECIFIED
Keck Institute for Space Studies (KISS)UNSPECIFIED
Subject Keywords:crop productivity; carbon fluxes; Earth observation; carbon modeling; spaceborne spectroscopy
Issue or Number:14
PubMed Central ID:PMC3986187
Record Number:CaltechAUTHORS:20160219-152530118
Persistent URL:
Official Citation:Luis Guanter, Yongguang Zhang, Martin Jung, Joanna Joiner, Maximilian Voigt, Joseph A. Berry, Christian Frankenberg, Alfredo R. Huete, Pablo Zarco-Tejada, Jung-Eun Lee, M. Susan Moran, Guillermo Ponce-Campos, Christian Beer, Gustavo Camps-Valls, Nina Buchmann, Damiano Gianelle, Katja Klumpp, Alessandro Cescatti, John M. Baker, and Timothy J. Griffis Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence PNAS 2014 111 (14) E1327-E1333; published ahead of print March 25, 2014, doi:10.1073/pnas.1320008111
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:64614
Deposited By: Colette Connor
Deposited On:20 Feb 2016 01:01
Last Modified:10 Nov 2021 23:33

Repository Staff Only: item control page