A Method to Reconstruct the Solar-Induced Canopy Fluorescence Spectrum from Hyperspectral Measurements

Performance of Ground-Based Solar-Induced Chlorophyll Fluorescence Retrieval Algorithms at the Water Vapor Absorption Band

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.

Relationship between Photosynthetic CO2 Assimilation and Chlorophyll Fluorescence for Winter Wheat under Water Stress

Solar-induced chlorophyll fluorescence (SIF) has a high correlation with Gross Primary Production (GPP). However, studies focusing on the impact of drought on the SIF-GPP relationship have had mixed results at various scales, and the mechanisms controlling the dynamics between photosynthesis and fluorescence emission under water stress are not well understood. We developed a leaf-scale measurement system to perform concurrent measurements of active and passive fluorescence, and gas-exchange rates for winter wheat experiencing a one-month progressive drought. Our results confirmed that: (1) shifts in light energy allocation towards decreasing photochemistry (the quantum yields of photochemical quenching in PSII decreased from 0.42 to 0.21 under intermediate light conditions) and increasing fluorescence emissions (the quantum yields of fluorescence increased to 0.062 from 0.024) as drought progressed enhance the degree of nonlinearity of the SIF-GPP relationship, and (2) SIF alone has a limited capacity to track changes in the photosynthetic status of plants under drought conditions. However, by incorporating the water stress factor into a SIF-based mechanistic photosynthesis model, we show that drought-induced variations in a variety of key photosynthetic parameters, including stomatal conductance and photosynthetic CO2 assimilation, can be accurately estimated using measurements of SIF, photosynthetically active radiation, air temperature, and soil moisture as inputs. Our findings provide the experimental and theoretical foundations necessary for employing SIF mechanistically to estimate plant photosynthetic activity during periods of drought stress.

A New Method for Winter Wheat Mapping Based on Spectral Reconstruction Technology

Timely and accurate estimation of the winter wheat planting area and its spatial distribution is essential for the implementation of crop growth monitoring and yield estimation, and hence for the development of national agricultural production and food security. In remotely sensed winter wheat mapping based on spectral similarity, the reference curve is obtained by averaging multiple standard curves, which limits mapping accuracy. We propose a spectral reconstruction method based on singular value decomposition (SR-SVD) for winter wheat mapping based on the unique growth characteristics of crops. Using Sentinel-2 A/B satellite data, we tested the SR-SVD method in Puyang County, and Shenzhou City, China. Performance was increased, with the optimal overall accuracy and the Kappa of Puyang County and Shenzhou City were 99.52% and 0.99, and 98.26% and 0.97, respectively. We selected the spectral angle mapper (SAM) and Euclidean Distance (ED) as the similarity measures. Compared to spectral similarity methods, the SR-SVD method significantly improves mapping accuracy, as it avoids excessive extraction, can identify more detailed information, and is advantageous in distinguishing non-winter wheat pixels. Three commonly used supervised classification methods, support vector machine (SVM), maximum likelihood (ML), and minimum distance (MD) were used for comparison. Results indicate that SR-SVD has the highest mapping accuracy and greatly reduces the number of misidentified pixels. Therefore, the SR-SVD method can achieve high-precision crop mapping and provide technical support for monitoring regional crop planting structure information.

Review of Top-of-Canopy Sun-Induced Fluorescence (SIF) Studies from Ground, UAV, Airborne to Spaceborne Observations

Remote sensing (RS) of sun-induced fluorescence (SIF) has emerged as a promising indicator of photosynthetic activity and related stress from the leaf to the ecosystem level. The implementation of modern RS technology on SIF is highly motivated by the direct link of SIF to the core of photosynthetic machinery. In the last few decades, a lot of studies have been conducted on SIF measurement techniques, retrieval algorithms, modeling, application, validation, and radiative transfer processes, incorporating different RS observations (i.e., ground, unmanned aerial vehicle (UAV), airborne, and spaceborne). These studies have made a significant contribution to the enrichment of SIF science over time. However, to realize the potential of SIF and to explore its full spectrum using different RS observations, a complete document of existing SIF studies is needed. Considering this gap, we have performed a detailed review of current SIF studies from the ground, UAV, airborne, and spaceborne observations. In this review, we have discussed the in-depth interpretation of each SIF study using four RS platforms. The limitations and challenges of SIF studies have also been discussed to motivate future research and subsequently overcome them. This detailed review of SIF studies will help, support, and inspire the researchers and application-based users to consider SIF science with confidence.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF - especially from space - is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using highly-resolved spectral sensors and state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing.

A Spectral Fitting Algorithm to Retrieve the Fluorescence Spectrum from Canopy Radiance

Retrieval of Sun-Induced Chlorophyll Fluorescence (F) spectrum is one of the challenging perspectives for further advancing F studies towards a better characterization of vegetation structure and functioning. In this study, a simplified Spectral Fitting retrieval algorithm suitable for retrieving the F spectrum with a limited number of parameters is proposed (two parameters for F). The novel algorithm is developed and tested on a set of radiative transfer simulations obtained by coupling SCOPE and MODTRAN5 codes, considering different chlorophyll content, leaf area index and noise levels to produce a large variability in fluorescence and reflectance spectra. The retrieval accuracy is quantified based on several metrics derived from the F spectrum (i.e., red and far-red peaks, O2 bands and spectrally-integrated values). Further, the algorithm is employed to process experimental field spectroscopy measurements collected over different crops during a long-lasting field campaign. The reliability of the retrieval algorithm on experimental measurements is evaluated by cross-comparison with F values computed by an independent retrieval method (i.e., SFM at O2 bands). For the first time, the evolution of the F spectrum along the entire growing season for a forage crop is analyzed and three diverse F spectra are identified at different growing stages. The results show that red F is larger for young canopy; while red and far-red F have similar intensity in an intermediate stage; finally, far-red F is significantly larger for the rest of the season.

Estimation of Chlorophyll Fluorescence at Different Scales: A Review

Measuring chlorophyll fluorescence is a direct and non-destructive way to monitor vegetation. In this paper, the fluorescence retrieval methods from multiple scales, ranging from near the ground to the use of space-borne sensors, are analyzed and summarized in detail. At the leaf-scale, the chlorophyll fluorescence is measured using active and passive technology. Active remote sensing technology uses a fluorimeter to measure the chlorophyll fluorescence, and passive remote sensing technology mainly depends on the sun-induced chlorophyll fluorescence filling in the Fraunhofer lines or oxygen absorptions bands. Based on these retrieval principles, many retrieval methods have been developed, including the radiance-based methods and the reflectance-based methods near the ground, as well as physically and statistically-based methods that make use of satellite data. The advantages and disadvantages of different approaches for sun-induced chlorophyll fluorescence retrieval are compared and the key issues of the current sun-induced chlorophyll fluorescence retrieval algorithms are discussed. Finally, conclusions and key problems are proposed for the future research.