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Open AccessArticle

Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity

1
Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Wilhelm-Johnen Straße, Jülich 52428, Germany
2
Remote Sensing Laboratories, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland
3
Institute of Geophysics and Meteorology, University of Cologne, Zülpicher Str. 49, Köln 50674, Germany
4
Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Wilhelm-Johnen Straße, Jülich 52428, Germany
5
Institute of Bio- and Geosciences, IBG-3: Agrosphere, Forschungszentrum Jülich GmbH, Wilhelm-Johnen Straße, Jülich 52428, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Jose Moreno and Prasad S. Thenkabail
Remote Sens. 2016, 8(7), 574; https://doi.org/10.3390/rs8070574
Received: 14 February 2016 / Revised: 6 June 2016 / Accepted: 30 June 2016 / Published: 8 July 2016
Sun-induced chlorophyll fluorescence (F) is a novel remote sensing parameter providing an estimate of actual photosynthetic rates. A combination of this new observable and Monteith’s light use efficiency (LUE) concept was suggested for an advanced modeling of gross primary productivity (GPP). In this demonstration study, we evaluate the potential of both F and the more commonly used photochemical reflectance index (PRI) to approximate the LUE term in Monteith’s equation and eventually improve the forward modeling of GPP diurnals. Both F and the PRI were derived from ground and airborne based spectrometer measurements over two different crops. We demonstrate that approximating dynamic changes of LUE using F and PRI significantly improves the forward modeling of GPP diurnals. Especially in sugar beet, a changing photosynthetic efficiency during the day was traceable with F and incorporating F in the forward modeling significantly improved the estimation of GPP. Airborne data were projected to produce F and PRI maps for winter wheat and sugar beet fields over the course of one day. We detected a significant variability of both, F and the PRI within one field and particularly between fields. The variability of F and PRI was higher in sugar beet, which also showed a physiological down-regulation of leaf photosynthesis. Our results underline the potential of F to serve as a superior indicator for the actual efficiency of the photosynthetic machinery, which is linked to physiological responses of vegetation. View Full-Text
Keywords: spectroscopy; sun-induced chlorophyll fluorescence; F760; gross primary productivity; GPP; vegetation; photosynthesis; PRI spectroscopy; sun-induced chlorophyll fluorescence; F760; gross primary productivity; GPP; vegetation; photosynthesis; PRI
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MDPI and ACS Style

Schickling, A.; Matveeva, M.; Damm, A.; Schween, J.H.; Wahner, A.; Graf, A.; Crewell, S.; Rascher, U. Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity. Remote Sens. 2016, 8, 574.

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