Location: Crop Production Systems ResearchTitle: Reconstruction of the full spectrum of solar-induced chlorophyll fluorescence: Intercomparison study for a novel method.
|ZHAO, FENG - Beihang University|
|LI, RONG - Beihang University|
|VERHOEF, WOUT - University Of Twente|
|COGLIATI, SERGIO - University Of Milano|
|LIU, XINJIE - Chinese Academy Of Sciences|
|GUO, YIQING - University Of Wales|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/14/2018
Publication Date: 10/18/2018
Citation: Zhao, F., Li, R., Verhoef, W., Cogliati, S., Liu, X., Huang, Y., Guo, Y. 2018. Reconstruction of the full spectrum of solar-induced chlorophyll fluorescence: Intercomparison study for a novel method. Remote Sensing of Environment. 219:233-246.
Interpretive Summary: Solar-induced chlorophyll fluorescence is an optical signal that can be used as an early and non-invasive indicator of the functioning and status of vegetation with photosynthesis. Scientists of Beihang University, Beijing, China and USDA ARS Crop Production Systems Research Unit at Stoneville, Mississippi began to investigate chlorophyll fluorescence for early detection of crop injury from glyphosate sprays in 2013. Now scientists from University of Twente in Netherlands, University of Milano-Bicocca in Italy, Chinese Academy of Sciences and University of New South Wales in Australia join the effort to study the physical mechanism of solar-induced chlorophyll fluorescence linked to photosynthesis of plants through mathematical models. This research establishes and compares the full spectrum of solar-induced chlorophyll fluorescence with innovative optical signal reconstruction algorithms by mathematical simulation and field data validation. The results are valuable for better understanding of solar-induced chlorophyll fluorescence measured in field for detection of crop stress caused by multiple factors.
Technical Abstract: Solar-induced chlorophyll fluorescence (SIF) can serve as an early and non-invasive indicator of the functioning and status of vegetation due to its close link to photosynthetic efficiency. Most existing approaches retrieve SIF by different implementations of the Fraunhofer Line Depth (FLD) principle at the O2-A and O2-B atmospheric absorption lines. However, the full SIF spectrum can provide more information on the functional status of photosynthetic machinery. European Space Agency’s FLuorescence EXplorer (FLEX) mission, to be launched in 2022, is dedicated to the accurate reconstruction of the full SIF spectrum over land and incorporates the heights and positions of the two SIF peaks and the total fluorescence emission (spectrally-integrated value) into planned Level-2 products. In this paper, the accuracies of four SIF spectrum reconstruction algorithms, with the Fluorescence Spectrum Reconstruction (FSR) method, the Full-spectrum Spectral Fitting Method (F-SFM), the SpecFit method, and the advanced Fluorescence Spectrum Reconstruction method (aFSR), respectively, are investigated by simulated and experimental datasets. The aFSR method is newly proposed in the research of this paper by capitalizing on the features of the existing methods. The new method uses linear combinations of basis spectra to approximate the spectra of SIF and reflectance factor, and exploits all available bands within the spectral range of SIF emission for spectral fitting of SIF and reflected radiance. The number of basis spectra of reflectance factor used is self-adaptively determined based on the Bayesian information criterion. For evaluation, we investigated the impact of spectral resolution (SR), signal-to-noise ratio (SNR), atmospheric correction, canopy structure, leaf biochemical parameters and directional effect on the SIF spectrum reconstruction accuracies of the four algorithms, and discussed the merits and limitations of each method. With high spectral resolving power and SNR (e.g., SR = 0.3 nm and SNR = 700), all methods can reconstruct SIF spectrum with an accuracy standard for the product of spectrally-integrated SIF set by the FLEX mission, i.e. average absolute relative error < 10%. The highest reconstruction accuracy is generally provided by aFSR, followed successively by F-SFM, FSR, and SpecFit. SR, SNR, atmospheric effect, and hot spot effect all influence the SIF spectrum reconstruction accuracy. However, the influence of canopy structure on the accuracy of the aFSR, F-SFM, and FSR methods is negligible. For experimental datasets, the SIF spectra reconstructed by all four methods agreed well with former studies in their shapes, magnitudes and diurnal variations. The spectra reconstructed by different algorithms were in agreement with each other: the coefficient of determination between the reconstruction results of each method and the average of the SIF spectra reconstructed through the four methods is higher than 0.94.