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Sun-Induced Chlorophyll Fluorescence I: Instrumental Considerations for Proximal Spectroradiometers

Sun-Induced Chlorophyll Fluorescence III: Benchmarking Retrieval Methods and Sensor Characteristics for Proximal Sensing

Laboratory for Earth Observation, Image Processing Laboratory, University of Valencia, C/Catedrático José Beltrán, 2, 46980 Paterna, Spain
Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425 Jülich, Germany
Centre of Excellence PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, 2610 Wilrijk, Belgium
Remote Sensing Laboratories, Department of Geography, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
Department of Surface Waters—Research and Management, Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco 56237, Mexico
Centro de Tecnologías Físicas, Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain
Remote Sensing of Environmental Dynamics Lab., DISAT, University of Milano-Bicocca, 48 P.zza della Scienza 1, 20126 Milano, Italy
Finnish Meteorological Institute, Erik Palmenin Aukio 1, P.O. Box 501, FI-00101 Helsinki, Finland
JB Hyperspectral Devices, Am Botanischen Garten 33, 40225 Düsseldorf, Germany
Laboratory of Dynamics Meteorology, Ecole Polytechnique, F-91128 Palaiseau, France
Crop Science, Institute of Agricultural Sciences, ETH Zurich, Universitätstrasse 2, 8092 Zurich, Switzerland
Max Planck Institute for Biogeochemistry, Hanks Knöll Straße 10, D-07745 Jena, Germany
GeoSciences University of Edinburgh, King’s Buildings, Edinburgh, Scotland 53 EH9 3FF, UK
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(8), 962;
Received: 1 March 2019 / Revised: 16 April 2019 / Accepted: 17 April 2019 / Published: 22 April 2019
The interest of the scientific community on the remote observation of sun-induced chlorophyll fluorescence (SIF) has increased in the recent years. In this context, hyperspectral ground measurements play a crucial role in the calibration and validation of future satellite missions. For this reason, the European cooperation in science and technology (COST) Action ES1309 OPTIMISE has compiled three papers on instrument characterization, measurement setups and protocols, and retrieval methods (current paper). This study is divided in two sections; first, we evaluated the uncertainties in SIF retrieval methods (e.g., Fraunhofer line depth (FLD) approaches and spectral fitting method (SFM)) for a combination of off-the-shelf commercial spectrometers. Secondly, we evaluated how an erroneous implementation of the retrieval methods increases the uncertainty in the estimated SIF values. Results show that the SFM approach applied to high-resolution spectra provided the most reliable SIF retrieval with a relative error (RE) ≤6% and <5% for F687 and F760, respectively. Furthermore, although the SFM was the least affected by an inaccurate definition of the absorption spectral window (RE = 5%) and/or interpolation strategy (RE = 15–30%), we observed a sensitivity of the SIF retrieval for the simulated training data underlying the SFM model implementation. View Full-Text
Keywords: sun-induced chlorophyll fluorescence; ground spectrometers; retrieval methods sun-induced chlorophyll fluorescence; ground spectrometers; retrieval methods
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MDPI and ACS Style

Cendrero-Mateo, M.P.; Wieneke, S.; Damm, A.; Alonso, L.; Pinto, F.; Moreno, J.; Guanter, L.; Celesti, M.; Rossini, M.; Sabater, N.; Cogliati, S.; Julitta, T.; Rascher, U.; Goulas, Y.; Aasen, H.; Pacheco-Labrador, J.; Mac Arthur, A. Sun-Induced Chlorophyll Fluorescence III: Benchmarking Retrieval Methods and Sensor Characteristics for Proximal Sensing. Remote Sens. 2019, 11, 962.

AMA Style

Cendrero-Mateo MP, Wieneke S, Damm A, Alonso L, Pinto F, Moreno J, Guanter L, Celesti M, Rossini M, Sabater N, Cogliati S, Julitta T, Rascher U, Goulas Y, Aasen H, Pacheco-Labrador J, Mac Arthur A. Sun-Induced Chlorophyll Fluorescence III: Benchmarking Retrieval Methods and Sensor Characteristics for Proximal Sensing. Remote Sensing. 2019; 11(8):962.

Chicago/Turabian Style

Cendrero-Mateo, M. P., Sebastian Wieneke, Alexander Damm, Luis Alonso, Francisco Pinto, Jose Moreno, Luis Guanter, Marco Celesti, Micol Rossini, Neus Sabater, Sergio Cogliati, Tommaso Julitta, Uwe Rascher, Yves Goulas, Helge Aasen, Javier Pacheco-Labrador, and Alasdair Mac Arthur. 2019. "Sun-Induced Chlorophyll Fluorescence III: Benchmarking Retrieval Methods and Sensor Characteristics for Proximal Sensing" Remote Sensing 11, no. 8: 962.

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