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Updated: May 28, 2025

Evaluation of Photosynthetic Behaviors by Simultaneous Measurements of Leaf Reflectance and Chlorophyll Fluorescence Analyses
Published on: August 9, 2019
Performance of Ground-Based Solar-Induced Chlorophyll Fluorescence Retrieval Algorithms at the Water Vapor Absorption
Yongqi Zhang1,2,3, Xinjie Liu2,3, Shanshan Du2,3
1College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China.
Abstract:
Solar-induced chlorophyll fluorescence (SIF) is essential for monitoring vegetation photosynthesis. The water vapor absorption band, the broadest absorption window, has a deeper absorption line than the O2-B band, providing significant potential for SIF retrieval; however, substantial variation in atmospheric water vapor column concentrations limits research on SIF retrieval using this band. This study evaluates seven common SIF retrieval algorithms, including sFLD, 3FLD, iFLD, pFLD, SFM, SVD, and DOAS, using simulated datasets under varying atmospheric water vapor concentrations, spectral resolution (SR), and signal-to-noise ratios (SNRs). Additionally, the SIF retrieval results from the H2O, O2-B, and O2-A absorption bands are compared and analyzed to explore the fluorescence retrieval potential of the water vapor band. Furthermore, the potential of commonly used spectrometers, including Ocean Optics QE Pro and ASD FieldSpec 3, for SIF retrieval using the water vapor absorption band was evaluated. The results were further validated using ground-based tower observations. The results show that sFLD consistently overestimates SIF in the water vapor band, limiting its reliability, while SFM performs best across varying conditions. In comparison, 3FLD and pFLD, along with SVD, are accurate at high resolutions but less effective at lower ones. iFLD performs relatively poorly overall, whereas DOAS excels in low SR retrievals. At the same time, our study also shows that the water vapor band offers higher accuracy in ground-based SIF retrieval compared to the O2-B band, demonstrating strong application potential and providing valuable references for selecting SIF retrieval algorithms.
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