[1657] - Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity

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Schickling, A., Matveeva, M., Damm, A., Schween, J., Wahner, A., Graf, A., Crewell, S., Rascher, U., 2016. Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity. Remote Sensing, 574 (8), 1 - 18. DOI: 10.3390/rs8070574.
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Title(s):Main Title: Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity
Description(s):Abstract: 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.
Identifier(s):DOI: 10.3390/rs8070574
Responsible Party
Creator(s):Author: Anke Schickling
Author: Maria Matveeva
Author: Alexander Damm
Author: Jan Schween
Author: Andreas Wahner
Author: Alexander Graf
Author: Susanne Crewell
Author: Uwe Rascher
TR32 Topic:Vegetation
Related Sub-project(s):D2
Subject(s):CRC/TR32 Keywords: Spectroscopy, Chlorophyll Fluorescence, GPP, Vegetation, Photosynthesis
File Details
File Name:Schickling_et_al_2016.pdf
Data Type:Text
Size(s):18 Pages
File Size:3984 kB (3.891 MB)
Date(s):Date Accepted: 2016-06-30
Available: 2016-07-08
Mime Type:application/pdf
Data Format:PDF
Download Permission:Free
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
North:-no map data
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Publication
Article Type:Journal
Source:Remote Sensing
Number Of Pages:18
Page Range:1 - 18
Metadata Details
Metadata Creator:Tanja Kramm
Metadata Created:2017-05-26
Metadata Last Updated:2017-05-26
Funding Phase:3
Metadata Language:English
Metadata Version:V41
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Dataset Downloads:1
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