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Article

Can Vegetation Indices Serve as Proxies for Potential Sun-Induced Fluorescence (SIF)? A Fuzzy Simulation Approach on Airborne Imaging Spectroscopy Data

1
Laboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental Engineering and Mechanical Engineering, Poznań University of Life Sciences, 60-649 Poznań, Poland
2
Remote Sensing Laboratories (RSL), Department of Geography, University of Zürich, 8057 Zürich, Switzerland
3
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands
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Department of Earth and Environmental Sciences, University of Milano-Bicocca, 20126 Milano, Italy
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Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425 Jülich, Germany
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Department of Hydrobiology, Faculty of Biology, Adam Mickiewicz University in Poznań, Uniwersytetu Poznańskiego 6, 61-614 Poznań, Poland
*
Author to whom correspondence should be addressed.
Academic Editor: Fabienne Maignan
Remote Sens. 2021, 13(13), 2545; https://doi.org/10.3390/rs13132545
Received: 10 May 2021 / Revised: 18 June 2021 / Accepted: 23 June 2021 / Published: 29 June 2021
(This article belongs to the Special Issue Remote Sensing of Fluorescence, Photosynthesis and Vegetation Status)
In this study, we are testing a proxy for red and far-red Sun-induced fluorescence (SIF) using an integrated fuzzy logic modelling approach, termed as SIFfuzzy and SIFfuzzy-APAR. The SIF emitted from the core of the photosynthesis and observed at the top-of-canopy is regulated by three major controlling factors: (1) light interception and absorption by canopy plant cover; (2) escape fraction of SIF photons (fesc); (3) light use efficiency and non-photochemical quenching (NPQ) processes. In our study, we proposed and validated a fuzzy logic modelling approach that uses different combinations of spectral vegetation indices (SVIs) reflecting such controlling factors to approximate the potential SIF signals at 760 nm and 687 nm. The HyPlant derived and field validated SVIs (i.e., SR, NDVI, EVI, NDVIre, PRI) have been processed through the membership transformation in the first stage, and in the next stage the membership transformed maps have been processed through the Fuzzy Gamma simulation to calculate the SIFfuzzy. To test whether the inclusion of absorbed photosynthetic active radiation (APAR) increases the accuracy of the model, the SIFfuzzy was multiplied by APAR (SIFfuzzy-APAR). The agreement between the modelled SIFfuzzy and actual SIF airborne retrievals expressed by R2 ranged from 0.38 to 0.69 for SIF760 and from 0.85 to 0.92 for SIF687. The inclusion of APAR improved the R2 value between SIFfuzzy-APAR and actual SIF. This study showed, for the first time, that a diverse set of SVIs considered as proxies of different vegetation traits, such as biochemical, structural, and functional, can be successfully combined to work as a first-order proxy of SIF. The previous studies mainly included the far-red SIF whereas, in this study, we have also focused on red SIF along with far-red SIF. The analysis carried out at 1 m spatial resolution permits to better infer SIF behaviour at an ecosystem-relevant scale. View Full-Text
Keywords: sun-induced fluorescence; SIFfuzzy; SIFfuzzy-APAR; spectral vegetation indices; HyPlant; fuzzy logic modelling sun-induced fluorescence; SIFfuzzy; SIFfuzzy-APAR; spectral vegetation indices; HyPlant; fuzzy logic modelling
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    Description: Supplementary material includes: 1. SM1_FUZZY logic approach. 2. SM2_Performance of SIFfuzzy-APAR 3. Figure S1 4. Figure S2 5. Figure S3
MDPI and ACS Style

Bandopadhyay, S.; Rastogi, A.; Cogliati, S.; Rascher, U.; Gąbka, M.; Juszczak, R. Can Vegetation Indices Serve as Proxies for Potential Sun-Induced Fluorescence (SIF)? A Fuzzy Simulation Approach on Airborne Imaging Spectroscopy Data. Remote Sens. 2021, 13, 2545. https://doi.org/10.3390/rs13132545

AMA Style

Bandopadhyay S, Rastogi A, Cogliati S, Rascher U, Gąbka M, Juszczak R. Can Vegetation Indices Serve as Proxies for Potential Sun-Induced Fluorescence (SIF)? A Fuzzy Simulation Approach on Airborne Imaging Spectroscopy Data. Remote Sensing. 2021; 13(13):2545. https://doi.org/10.3390/rs13132545

Chicago/Turabian Style

Bandopadhyay, Subhajit, Anshu Rastogi, Sergio Cogliati, Uwe Rascher, Maciej Gąbka, and Radosław Juszczak. 2021. "Can Vegetation Indices Serve as Proxies for Potential Sun-Induced Fluorescence (SIF)? A Fuzzy Simulation Approach on Airborne Imaging Spectroscopy Data" Remote Sensing 13, no. 13: 2545. https://doi.org/10.3390/rs13132545

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