Sun-induced Chlorophyll Fluorescence Measurements Research Articles

Hybrid Machine Learning and Geostatistical Methods for Gap Filling and Predicting Solar-Induced Fluorescence Values

Sun-induced chlorophyll fluorescence (SIF) has proven to be advantageous in estimating gross primary production, despite the lack of a stable relationship. Satellite-based SIF measurements at Level 2 offer comprehensive global coverage and are available in near real time. However, these measurements are often limited by spatial and temporal sparsity, as well as discontinuities. These limitations primarily arise from incomplete satellite trajectories. Additionally, variability in cloud cover and periodic issues specific to the instruments can compromise data quality. Two families of methods have been developed to address data discontinuity: (1) machine learning-based gap-filling techniques and (2) geostatistical techniques (various forms of kriging). The former techniques utilize the relationships between ancillary data and SIF, while the latter usually rely on the available SIF data recordings and their covariance structure to provide estimates at unsampled locations. In this study, we create a synthetic approach for SIF gap filling by hybridizing the two approaches under the umbrella of kriging with external drift. We performed leave-one-out cross-validation of the OCO-2 SIF retrieval aggregates for the entire year of 2019, comparing three methods: ordinary kriging, ML-based estimation using ancillary data, and kriging with external drift. The Mean Absolute Error (MAE) for ML, ordinary kriging, and the hybrid approach was found to be 0.1399, 0.1318, and 0.1183 mW m2 sr−1 nm−1, respectively. We demonstrate that the performance of the hybrid approach exceeds both parent techniques due to the incorporation of information from multiple resources. This use of multiple datasets enriches the hybrid model, making it more robust and accurate in handling the spatio-temporal variability and discontinuity of SIF data. The developed framework is portable and can be applied to SIF retrievals at various resolutions and from various sources (satellites), as well as extended to other satellite-measured variables.

The relationship between wheat yield and sun-induced chlorophyll fluorescence from continuous measurements over the growing season

Rapid and accurate estimation of crop yield using remote sensing technology could be an important tool for improved global food security. As an effective probe measuring photosynthesis, sun-induced chlorophyll fluorescence (SIF) has potential for predicting crop yield, particularly when SIF measurements are integrated over an extended time period. However, few studies have investigated how temporal scale, vegetation structure, physiology and environmental factors affect crop yield prediction using SIF. Therefore, in this study we evaluate uncertainties in the relationship between SIF and wheat yield, associated with changes in leaf area index (LAI), chlorophyll a and b content (Cab), photosynthetic active radiation (PAR), and the timing of measurements over a range of temporal scales. Wheat field experiments were carried out over two years. LAI, Cab, PAR and canopy SIF were measured at several temporal scales. We systematically compared the performance of SIF parameters [near-infrared canopy SIF normalized by PAR (SIFyNIR), total near-infrared at photosystem level normalized by PAR (SIFyNIR_tot), and normalized difference fluorescence index (NDFI)] and vegetation indices (VIs) [normalized difference vegetation index (NDVI), and NIR reflectance of vegetation (NIRv)] as predictors of yield estimation. Among the SIF parameters, NDFI appeared to be the most sensitive to LAI and Cab. SIFyNIR_tot at the anthesis stage was the best predictor of wheat yield. SIF outperformed VIs for wheat yield estimation during the late growth period. Moreover, as the temporal scale increased (i.e., as the data values were accumulated over longer intervals of time), the relationship between SIFyNIR and wheat yield tended to be more linear. Overall, the uncertainty in the relationship between SIF and yield was affected more by LAI than Cab, and higher PAR produced a stronger and more stable relationship between SIF and wheat yield. Our findings provide empirical support and an example of an approach for using SIF to predict crop yield, as well as elucidation of the mechanisms underlying the relationship between SIF and production.

Decoupling physiological and non-physiological responses of sugar beet to water stress from sun-induced chlorophyll fluorescence

Due to the physiological connection with photosynthesis, sun-induced chlorophyll fluorescence (SIF) provides a promising indicator of vegetation physiological changes caused by environmental stress (e.g. water deficiency). SIF response to crop physiological alterations under water stress is complicated by concurrent non-physiological changes. The non-physiological variation stems from crop structure, leaf optical traits (i.e. pigments, leaf water content, and dry matter), and sun-target geometry. This study aims to disentangle the physiological effect from the non-physiological effect on SIF variations caused by water stress, providing more direct insights into the mechanism of SIF response to stress. We parameterized the radiative transfer model (RTM) SCOPE with top-of-canopy (TOC) reflectance and SIF measurements to decouple the joint effects on TOC SIF in sugar beet. SIF and reflectance data were acquired over irrigated and water-stressed plots using an Unmanned Aerial Vehicle (UAV) on two consecutive days. The non-physiological response was quantified with SCOPE by fitting the model parameters to the TOC reflectance measurements. Subsequently, fluorescence emission yield (ΦF) was estimated using SIF measurements to represent the actual physiological status. The results demonstrate that SIF variation caused by water stress both at 687 nm and 760 nm was affected by both the physiological alterations in ΦF and the non-physiological changes. At both 687 nm and 760 nm, the non-physiological contribution to SIF variations was lower than the contribution of ΦF variation induced by water stress. The lower non-physiological contribution was mainly due to the weak combined effect of the fraction of photosynthetically active radiation absorbed by leaf chlorophyll (fAPARchl) and the fluorescence escape fraction (fesc) on SIF responses. This study provided direct insights into the plant physiological status under water stress and further indicated the ability of the approach of combining RTMs, canopy reflectance, and SIF measurements to support the scalable quantitative use of SIF from the leaf to the ecosystem level.

Comparison of a UAV- and an airborne-based system to acquire far-red sun-induced chlorophyll fluorescence measurements over structurally different crops

• Pronounced diurnal patterns found for both UAV- and Airborne-based far-red SIF. • Consistent spatial patterns of UAV- and Airborne-based far-red SIF over different crops. • FluorSpec far-red SIF is linearly related to HyPlant far-red SIF. • Far-red sun-induced chlorophyll fluorescence can be reliably measured from a UAV. Sun-induced chlorophyll fluorescence (SIF) is a promising proxy of the dynamic photosynthetic process. Unmanned Aerial Vehicles (UAVs) are flexible and cost-effective for acquiring SIF data at high temporal and spatial resolution. The UAV-based point spectrometer FluorSpec was designed to measure SIF within agricultural fields. To correctly understand SIF values and further photosynthetic research, the ability of the UAV-based FluorSpec to provide reliable SIF information within agricultural fields needs evaluation. In this paper, the UAV-based FluorSpec was compared with the high-performance airborne imaging spectrometer HyPlant using diurnal far-red SIF measurements over different crop types (i.e. two varieties of winter wheat, two varieties of spring barley, bean, and maize), which were acquired by almost simultaneous airborne and UAV flights during a clear sky day in 2019. After improving the footprint geolocation of FluorSpec measurements using concurrent red-green-blue (RGB) images, we compared the FluorSpec and HyPlant SIF measurements, their diurnal developments, and spatial distributions for different crop types. The results from both systems show consistent, clear diurnal patterns that are positively correlated with photosynthetically active radiation (PAR) over most crop types. Similar SIF spatial patterns were shown within crop fields as well. UAV-based FluorSpec SIF showed a good linear correlation with HyPlant SIF with an R 2 up to 0.76. The good agreement confirms that the UAV-based FluorSpec system is able to measure meaningful SIF values at the field scale and thus stimulates SIF applications in agriculture. The systematic errors up to 0.3 mW m −2 sr −1 nm −1 from the linear regression between the two systems indicate that the UAV-based FluorSpec system should be improved by considering the main sources of uncertainty discussed in this paper. Future studies with dedicated experiments are recommended to assess the systematic uncertainties of UAV-based FluorSpec derived SIF information.

Potential of UAV-based sun-induced chlorophyll fluorescence to detect water stress in sugar beet

• SIF parameters from a UAV were used to detect crop water stress. • UAV-based hyperspectral and thermal data assisted the interpretation of SIF response. • The selected SIF indicators were able to track drought recovery after irrigation. • The fluorescence emission yield was more sensitive to drought than the apparent SIF yield. Sun-induced chlorophyll fluorescence (SIF) is a direct indicator of plant photosynthetic activities and can potentially indicate plant physiological changes caused by water stress. However, the direct effect of water stress on the physiological SIF responses in crops at the field level still needs further research to clearly understand the involved mechanisms. To study this relationship, we made use of Unmanned Aerial Vehicles (UAVs), which are flexible and cost-effective to acquire SIF data at a high temporal resolution. We acquired near-infrared SIF (760 nm) and red SIF (687 nm) measurements using a UAV platform over irrigated and non-irrigated sugar beet plots. To represent physiological changes in crops, we calculated the apparent SIF yield (SIF normalized by the absorbed photosynthetically active radiation) at 760 and 687 nm (SIF 760yield and SIF 687yield ), the fluorescence emission yield at 760 nm (ΦF 760 ), and the SIF ratio (the ratio between SIF 687 and SIF 760 ). ΦF 760 was estimated using the recently developed NIRvH approach. For an improved interpretation of the response of these SIF indicators, we also acquired additional UAV-based hyperspectral and thermal data. We found that on June 28, when sugar beets were experiencing water stress, SIF 687yield , ΦF 760 , and SIF ratio all showed a significant response to the recovery of the irrigated sugar beets (p-value < 0.05). On the other hand, on July 24 when both water stress and heat stress affected the crop, only ΦF 760 and SIF ratio weakly tracked the changes induced by the irrigation (p-value < 0.1). ΦF 760 had similar changes to SIF 760yield in both June and July, but ΦF 760 was more sensitive to irrigation. This indicates the importance of correcting for the structural effect when interpreting the SIF response. The findings suggest that SIF indicators can indicate water stress at the field level, but its value to detect the changes of photosynthetic activities under severe stress needs more investigation.

Remote Sensing of Instantaneous Drought Stress at Canopy Level Using Sun-Induced Chlorophyll Fluorescence and Canopy Reflectance

Climate change amplifies the intensity and occurrence of dry periods leading to drought stress in vegetation. For monitoring vegetation stresses, sun-induced chlorophyll fluorescence (SIF) observations are a potential game-changer, as the SIF emission is mechanistically coupled to photosynthetic activity. Yet, the benefit of SIF for drought stress monitoring is not yet understood. This paper analyses the impact of drought stress on canopy-scale SIF emission and surface reflectance over a lettuce and mustard stand with continuous field spectrometer measurements. Here, the SIF measurements are linked to the plant’s photosynthetic efficiency, whereas the surface reflectance can be used to monitor the canopy structure. The mustard canopy showed a reduction in the biochemical component of its SIF emission (the fluorescence emission efficiency at 760 nm—ϵ760) as a reaction to drought stress, whereas its structural component (the Fluorescence Correction Vegetation Index—FCVI) barely showed a reaction. The lettuce canopy showed both an increase in the variability of its surface reflectance at a sub-daily scale and a decrease in ϵ760 during a drought stress event. These reactions occurred simultaneously, suggesting that sun-induced chlorophyll fluorescence and reflectance-based indices sensitive to the canopy structure provide complementary information. The intensity of these reactions depend on both the soil water availability and the atmospheric water demand. This paper highlights the potential for SIF from the upcoming FLuorescence EXplorer (FLEX) satellite to provide a unique insight on the plant’s water status. At the same time, data on the canopy reflectance with a sub-daily temporal resolution are a promising additional stress indicator for certain species.

The potential of spatial aggregation to extract remotely sensed sun-induced fluorescence (SIF) of small-sized experimental plots for applications in crop phenotyping

Airborne measurements of sun-induced chlorophyll fluorescence (SIF) are a promising tool for monitoring plant functioning on different scales. However, currently operational airborne imaging spectrometers for SIF measurements still have limited spatial resolution and pointing accuracy. This is challenging in terms of the practical use of SIF maps for crop breeding and plant phenotyping. We developed and tested two spatial aggregation approaches to make airborne SIF data usable in experimental settings with a high number of small experimental plots. The two aggregation approaches generating representative SIF values for experimental plots demonstrated the potential to be used in crop phenotyping. The first aggregation approach (Approach A) aggregates pixel values directly on SIF maps, whereas the second approach (Approach B) aggregates at-sensor radiance before SIF retrieval. The statistical analysis showed that Approaches A and B led to significantly different SIF products for single experimental plots (p < 0.001). To evaluate the usability of the two approaches, aggregated SIF products were fitted against ground-based reference measurements. We found that Approach B provided a better representation of ground truth SIF760 (R2 = 0.61, p < 0.001) than Approach A (R2 = 0.55, p < 0.001) when combined with weighted averaging and robust outlier detection. Furthermore, our results suggest that a slight decrease in the spatial resolution of the image data improves accuracy of aggregation.

Unpacking the drivers of diurnal dynamics of sun-induced chlorophyll fluorescence (SIF): Canopy structure, plant physiology, instrument configuration and retrieval methods

Sun-induced chlorophyll fluorescence (SIF) from spaceborne sensors is a promising tool for global carbon cycle monitoring, but its application is constrained by insufficient understanding of the drivers underlying diurnal SIF dynamics. SIF measurements from ground-based towers can reveal diurnal SIF dynamics across biomes and environmental conditions; however, meaningful interpretation of diurnal variations requires disentangling impacts from canopy structure, plant physiology, instrument configuration and retrieval methods, which often interact with and confound each other. This study aims to unpack these drivers using 1) concurrent ground and airborne canopy-scale and leaf-scale measurements at a corn field, 2) a mechanistic SIF model that explicitly considers the dynamics of photochemistry (via the fraction of open photosystem II reaction centers, qL) and photoprotection (via nonphotochemical quenching, NPQ) as well as their interactive dependence on the sub-canopy light environment, and 3) cross-comparison of SIF instrument configurations and retrieval methods. We found that crop row orientations and sun angles can introduce a distinctive midday dip in SIF in absence of stress, due to a midday drop of absorbed photosynthetically active radiation (APAR) when crop rows are north-south oriented. Canopy structure caused distinctive responses in both qL and NPQ at different positions within the vertical canopy that collectively influenced fluorescence quantum yield (ΦF) at the leaf scale. Once integrated at the canopy scale, diurnal dynamics of both APAR and canopy escape probability (ε) are critical for accurately shaping diurnal SIF variations. While leaf-level qL and NPQ exhibited strong diurnal dynamics, their influence was attenuated at the canopy scale due to opposing effects on SIF at different canopy layers. Furthermore, different system configurations (i.e., bi-hemispherical vs. hemispherical-conical) and retrieval methods can bias the SIF magnitude and distort its diurnal shapes, therefore confounding the interpretation of inherent strength and dynamics of SIF emission. Our findings demonstrate the importance of crop row structures, interactive variations in canopy structure and plant physiology, instrument configuration, and retrieval method in shaping the measured dynamics of diurnal SIF. This study highlights the necessity to account for these factors to accurately interpret satellite SIF, and informs future synthesis work with different SIF instrumentation and retrieval methods across sites.

Potential of Sun‐Induced Chlorophyll Fluorescence for Indicating Mangrove Canopy Photosynthesis

AbstractAccurate characterization of gross primary productivity (GPP) is critically important in assessing mangrove carbon budgets, but the current knowledge of the temporal variations of GPP in evergreen mangroves is very limited. Remote sensing of sun‐induced chlorophyll fluorescence (SIF) has emerged as a promising approach to approximating GPP across ecosystems, but its capability for tracking GPP in evergreen mangroves has not been assessed. The SIF‐GPP link at a subtropical mangrove and its environmental controls are explored using 1‐year time‐series measurements from tower‐based hyperspectral and eddy covariance systems. Both the relationship between SIF and GPP as well as that between SIFy (SIF yield: the ratio of SIF over absorbed photosynthetically active radiation [APAR]) and LUE (light use efficiency: the ratio of GPP over APAR) at diurnal and seasonal time scales are analyzed. The temporal variations of SIF and GPP shared overall similar changing patterns, but their functional relationship tended to be time scale‐dependent. Midday depressions in SIF were observed when environmental stresses occurred around noon (including excess light and high VPD), and the strength of the SIF‐GPP link was affected by changing environmental conditions. The SIFy‐LUE relationship was temporally more dynamic, tending to match during midday hours but diverge from each other during morning and afternoon hours. These findings confirm SIF can serve as a potential remotely sensed indicator of mangrove canopy photosynthesis. This paper provides the first, high temporal‐resolution, continuous SIF measurements in mangroves, and highlights the importance of the impacts of environmental conditions on the SIF‐GPP relationship.

Estimation of leaf nitrogen content and photosynthetic nitrogen use efficiency in wheat using sun-induced chlorophyll fluorescence at the leaf and canopy scales

Leaf nitrogen content (LNC), an indicator for the amount of photosynthetic proteins, plays an important role to understand plant function and status. In previous studies, vegetation indices (VIs) have been demonstrated to monitor LNC non-destructively, but which is influenced by backgrounds, and lacks specificity for nitrogen stress. In this study, sun-induced chlorophyll fluorescence (SIF), a novel technique related to plant physiology state, was proposed to estimate area-based and mass-based LNC at both leaf and canopy scales. In addition, SIF indices were evaluated to retrieve photosynthesis nitrogen use efficiency (PNUE), an important trait of leaf economics and physiology, based on the relationships between SIF, photosynthesis, and LNC.This study was conducted on two field experiments of winter wheat with different nitrogen regimes in Rugao, Jiangsu Province, China during 2016-2017 and 2017-2018 growing seasons. We took measurements of SIF, reflectance, biochemical and growth structural parameters at the leaf and canopy scales. The SIF signal was collected using ASD (Analytical Spectral Devices, Boulder, CO, USA) and QEpro (Ocean Optics, Dunedin, FL, USA) spectrometers at the two observational scales, with a full width at half maximum (FWHM) of 1.4 nm and 0.13 nm, respectively. SIF indices were calculated based on the SIF signal extracted at two oxygen absorption bands. Our results demonstrated that area-based LNC was better related to SIF indices and VIs than mass-based LNC. SIF ratio index (SIFR) and normalized SIF index (SIFN), defined as SIF761/SIF687 and (SIF761-SIF687)/(SIF761+SIF687) separately, performed better in monitoring area-based LNC at the two observation scales than CIred edge, which performed best in VIs group. Compared with CIred edge, the best estimation accuracy of SIF indices for area-based LNC increased by 0.08 and 0.02 at the leaf and canopy scales, separately. And when using SIFR and SIFN to monitor area-based LNC, there is no saturation phenomenon, which occurs using traditional VIs. From the whole range of data, area-based LNC was closely related to several plant traits (leaf: area-based leaf chlorophyll content (LCC) (LCCarea), leaf mass per area (LMA); canopy: area-based canopy LCC (CCCarea), leaf area index (LAI), leaf dry weight (LDW) per unit soil area, and LMA), which was consistent with previous studies. However, in specific group with fixed area-based LCC value, although area-based LNC almost wasn’t significantly correlated with these traits, SIFR and SIFN were instead always highly correlated with area-based LNC in each small datasets on two observation scales (leaf scale: R2>0.50, R2>0.46; canopy scale: R2>0.41, R2>0.42). Thus, the contribution of SIFR and SIFN to estimate area-based LNC wasn’t only the plant traits listed, but also other internal characters, like nitrogen allocation and proportion. Moreover, SIFR and SIFN were proved to be potential detectors to retrieve PNUE. These findings would provide us a new perspective for understanding plant nitrogen status from remote sensing observations, detecting plant function and managing precise agriculture.

Seasonal variations in the relationship between sun-induced chlorophyll fluorescence and photosynthetic capacity from the leaf to canopy level in a rice crop

Photosynthetic capacity (leaf maximum carboxylation rate, Vcmax) is a critical parameter for accurately assessing carbon assimilation by plant canopies. Recent studies of sun-induced chlorophyll fluorescence (SIF) have shown potential for estimating Vcmax at the ecosystem level. However, the relationship between SIF and Vcmax at the leaf and canopy levels is still poorly understood. In this study, we investigated the dynamic relationship between SIF and Vcmax and its controlling factors using SIF and CO2 response measurements in a rice paddy. We found that SIF and its yield (SIFy) were strongly correlated with Vcmax during the growing season, although the relationship varied with plant growth stages. After flowering, SIFy showed a stronger relationship with Vcmax than SIF flux at both the leaf and canopy levels. Further analysis suggested that the divergence of the link between SIF and Vcmax from leaf to canopy are the result of changes in canopy structure and leaf physiology, highlighting that these need to be considered when interpreting the SIF signal across spatial scales. Our results provide evidence that remotely sensed SIF observations can be used to track seasonal variations in Vcmax at the leaf and canopy levels.

Fluorescence Correction Vegetation Index (FCVI): A physically based reflectance index to separate physiological and non-physiological information in far-red sun-induced chlorophyll fluorescence

Sun-induced chlorophyll fluorescence (SIF) has been used to track vegetation photosynthetic activity for improving estimation of gross primary productivity (GPP) and detecting plant stress. There are both physical and physiological controls of SIF measured at the surface and retrieved from remote sensing including satellite observations. In order to accurately use SIF for monitoring of plant physiology, the effects of physically-based radiation processes related to leaf and canopy structure, notably photosynthetically active radiation (PAR) absorption and SIF scattering and re-absorption, must be characterized. In this study, we investigate both PAR absorption and SIF scattering processes and find that although it is difficult to quantify their effects individually by using just reflectance, the combined effects of the two processes can be well approximated by a reflectance index. This index, referred to as FCVI (Fluorescence Correction Vegetation Index), is defined as the difference between near-infrared (NIR) and broad-band visible (VIS, 400–700 nm) reflectance acquired under identical sun-canopy-observer geometry of the SIF measurements. The development of the index was based on the physical connection between reflectance and far-red SIF, which was revealed by using the spectral invariant theory. The utility of FCVI to correct far-red SIF for PAR absorption and scattering effects, thus improving the link to photosynthesis, was tested with data from: (i) a field experiment for a growing season; and (ii) a numerical experiment which included a number of scenarios generated by a radiative transfer model. For both the observations and simulations, the FCVI provided a promising estimate of the impact of the physically-based radiation processes on far-red SIF of moderately dense canopies (i.e., FCVI ≥ 0.18). Normalizing the TOC far-red SIF by both the incident PAR (iPAR) and the FCVI provided a good estimate of the far-red fluorescence emission efficiency of the canopies examined. This approach enhances our ability to generalize retrievals for vegetation processes as they change through natural growth phases and seasons. Taken together, far-red SIF and FCVI may enable the assessment of the light partitioning of vegetation canopies, an essential step to facilitate the use of far-red SIF for tracking physiological processes.

Impacts of different radiometric calibration methods on the retrievals of sun-induced chlorophyll fluorescence and its relation to productivity for continuous field measurements

Sun-induced chlorophyll fluorescence (SIF), now observed from space on a global scale, has been shown to be a powerful proxy for photosynthetic activity. Long-term in situ field canopy SIF measurements are improving, enabling better understanding of SIF signal and support to satellite missions. Since SIF retrievals rely on the absolute irradiance radiance measurements, accurate outdoor radiometric calibration is necessary to provide accurate radiance data, especially for long-term continuous measurements on forest stands. However, standard laboratory calibration methods are not practical to be performed for outdoor long-term measurements, and several in-field alternative methods are generally used, which may result in some uncertainties. Here we evaluate the effects of different radiometric calibration methods on SIF retrievals and its relation with gross primary productivity (GPP) at the canopy level. Three widely used methods are used, i.e., well-established laboratory methods with integrating sphere, laboratory-calibrated reference spectrometer (ASD FieldSpec Pro), and a light calibration source with a white reference panel. Our results indicate that different radiometric calibrations have marginal effects on vegetation indices but have significant effects on the SIF absolute value, and have slight effects on diurnal and seasonal patterns of SIF. Moreover, the relationships between GPP and SIF retrieved using different calibration coefficients are similar at both diurnal and seasonal scales, but with different regression slopes. Therefore, we recommend that a standard laboratory radiometric calibration is conducted using an integrating sphere before installation in the field and a regular in-field calibration with a well-calibrated spectrometer and white reference, especially for long-term observation above a forest canopy. Our findings have strong implications for the ongoing and future ground canopy SIF measurements and suggest the need for a consistent radiometric calibration method, especially for cross-site comparison studies.

Using reflectance to explain vegetation biochemical and structural effects on sun-induced chlorophyll fluorescence

The growing availability of global measurements of sun-induced chlorophyll fluorescence (SIF) can help in improving crop monitoring, especially the monitoring of photosynthetic activity. However, variations in top-of-canopy (TOC) SIF cannot be directly interpreted as physiological changes because of the confounding effects of vegetation biochemistry (i.e. pigments, dry matter and water) and structure. In this study, we propose an approach of using radiative transfer models (RTMs) and TOC reflectance to estimate the biochemical and structural effects on TOC SIF, as a necessary step in retrieving physiological information from TOC SIF. The approach was assessed by using airborne (HyPlant) reflectance and SIF data acquired over an agricultural experimental farm in Germany on two days, before and during a heat event in summer 2015 with maximum temperatures of 27°C and 34°C, respectively. The results show that over 76% variation among different crops in SIF observations was explained by variation in vegetation biochemistry and structure. In addition, the changes of vegetation biochemistry and structure explained as much as 73% variation between the two days in far-red SIF, and 40% variation in red SIF. The remaining unexplained variation was mostly attributed to the variability in physiological status. We conclude that reflectance provides valuable information to account for biochemical and structural effects on SIF and to advance analysis of SIF observations. The combination of RTMs, reflectance and SIF opens new pathways to detect vegetation biochemical, structural and physiological changes.

Retrieval of Sun-Induced Chlorophyll Fluorescence Using Statistical Method Without Synchronous Irradiance Data

Remote sensing of top-of-canopy (TOC) long-term sun-induced chlorophyll fluorescence (SIF) is necessary to better understand the SIF-photosynthesis relationship. Statistical methods provide an alternative to TOC SIF retrieval, as they are independent of synchronous irradiance measurements and may better describe actual irradiance. This letter aims to evaluate the feasibility of using statistical methods for time series TOC SIF retrieval in the absence of synchronous irradiance measurements. Results show that the training set should include nonfluorescent radiance spectra under a variety of solar zenith angles, and that water vapor is an important contributor of spectral variation within 717–745 nm. On the diurnal scale, atmospheric features trained from irradiance spectra can be used to retrieve SIF values from high-frequency upwelling radiance spectra. Features independently trained from nonfluorescent radiance spectra measured on one day can be used for SIF retrieval on a different day within a relatively short period. Our results show that statistical methods have the potential to simplify ground-based SIF measurements and data processing.

Satellite chlorophyll fluorescence measurements reveal large-scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests.

Mid-to-high latitude forests play an important role in the terrestrial carbon cycle, but the representation of photosynthesis in boreal forests by current modelling and observational methods is still challenging. In particular, the applicability of existing satellite-based proxies of greenness to indicate photosynthetic activity is hindered by small annual changes in green biomass of the often evergreen tree population and by the confounding effects of background materials such as snow. As an alternative, satellite measurements of sun-induced chlorophyll fluorescence (SIF) can be used as a direct proxy of photosynthetic activity. In this study, the start and end of the photosynthetically active season of the main boreal forests are analysed using spaceborne SIF measurements retrieved from the GOME-2 instrument and compared to that of green biomass, proxied by vegetation indices including the Enhanced Vegetation Index (EVI) derived from MODIS data. We find that photosynthesis and greenness show a similar seasonality in deciduous forests. In high-latitude evergreen needleleaf forests, however, the length of the photosynthetically active period indicated by SIF is up to 6weeks longer than the green biomass changing period proxied by EVI, with SIF showing a start-of-season of approximately 1month earlier than EVI. On average, the photosynthetic spring recovery as signalled by SIF occurs as soon as air temperatures exceed the freezing point (2-3°C) and when the snow on the ground has not yet completely melted. These findings are supported by model data of gross primary production and a number of other studies which evaluated insitu observations of CO2 fluxes, meteorology and the physiological state of the needles. Our results demonstrate the sensitivity of space-based SIF measurements to light-use efficiency of boreal forests and their potential for an unbiased detection of photosynthetic activity even under the challenging conditions interposed by evergreen boreal ecosystems.

Comparison of Sun-Induced Chlorophyll Fluorescence Estimates Obtained from Four Portable Field Spectroradiometers

Remote Sensing of Sun-Induced Chlorophyll Fluorescence (SIF) is a research field of growing interest because it offers the potential to quantify actual photosynthesis and to monitor plant status. New satellite missions from the European Space Agency, such as the Earth Explorer 8 FLuorescence EXplorer (FLEX) mission—scheduled to launch in 2022 and aiming at SIF mapping—and from the National Aeronautics and Space Administration (NASA) such as the Orbiting Carbon Observatory-2 (OCO-2) sampling mission launched in July 2014, provide the capability to estimate SIF from space. The detection of the SIF signal from airborne and satellite platform is difficult and reliable ground level data are needed for calibration/validation. Several commercially available spectroradiometers are currently used to retrieve SIF in the field. This study presents a comparison exercise for evaluating the capability of four spectroradiometers to retrieve SIF. The results show that an accurate far-red SIF estimation can be achieved using spectroradiometers with an ultrafine resolution (less than 1 nm), while the red SIF estimation requires even higher spectral resolution (less than 0.5 nm). Moreover, it is shown that the Signal to Noise Ratio (SNR) plays a significant role in the precision of the far-red SIF measurements.

A Method for Uncertainty Assessment of Passive Sun-Induced Chlorophyll Fluorescence Retrieval Using an Infrared Reference Light

Measurements of sun-induced chlorophyll fluorescence (SIF) over plant canopies provide a proxy for plant photosynthetic capacity and are of high interest for plant research. Together with spectral reflectance, SIF has the potential to act as a noninvasive approach to quantify photosynthetic plant traits from field to air and spaceborne scales. However, SIF is a small signal contribution to the reflected sunlight and often not distinguishable from sensor noise. SIF estimation is, therefore, affected by an unquantified uncertainty, making it difficult to estimate accurately how much SIF is truly emitted from the plant. To investigate and overcome this, we designed a device based on a spectrometer covering the visible range and equipped it with an LED emitting at the wavelength of SIF. Using this as a reference and applying thorough calibrations, we present consistent evidence of the instrument's capability of SIF retrieval and accuracy estimations. The LED's intensity was measured under sunlight with 1.27 ± 0.27 mW × sr -1 m -2 nm -1 stable over the day. The large increase of SIF due to the Kautsky effect was measured spectrally and temporally proving the biophysical origin of the signal. We propose rigorous tests for instruments intended to measure SIF and show ways to further improve the presented methods.

Estimation of vegetation photosynthetic capacity from space‐based measurements of chlorophyll fluorescence for terrestrial biosphere models

Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (Vcmax ) is a key control parameter of photosynthetic capacity. Even though Vcmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes. Alternatively, recent space-borne measurements of sun-induced chlorophyll fluorescence (SIF) can offer an observational constraint on photosynthesis simulations. Here, we show that top-of-canopy SIF measurements from space are sensitive to Vcmax at the ecosystem level, and present an approach to invert Vcmax from SIF data. We use the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model to derive empirical relationships between seasonal Vcmax and SIF which are used to solve the inverse problem. We evaluate our Vcmax estimation method at six agricultural flux tower sites in the midwestern US using spaced-based SIF retrievals. Our Vcmax estimates agree well with literature values for corn and soybean plants (average values of 37 and 101μmolm(-2) s(-1) , respectively) and show plausible seasonal patterns. The effect of the updated seasonally varying Vcmax parameterization on simulated gross primary productivity (GPP) is tested by comparing to simulations with fixed Vcmax values. Validation against flux tower observations demonstrate that simulations of GPP and light use efficiency improve significantly when our time-resolved Vcmax estimates from SIF are used, with R(2) for GPP comparisons increasing from 0.85 to 0.93, and for light use efficiency from 0.44 to 0.83. Our results support the use of space-based SIF data as a proxy for photosynthetic capacity and suggest the potential for global, time-resolved estimates of Vcmax .

Forest productivity and water stress in Amazonia: observations from GOSAT chlorophyll fluorescence

It is unclear to what extent seasonal water stress impacts on plant productivity over Amazonia. Using new Greenhouse gases Observing SATellite (GOSAT) satellite measurements of sun-induced chlorophyll fluorescence, we show that midday fluorescence varies with water availability, both of which decrease in the dry season over Amazonian regions with substantial dry season length, suggesting a parallel decrease in gross primary production (GPP). Using additional SeaWinds Scatterometer onboard QuikSCAT satellite measurements of canopy water content, we found a concomitant decrease in daily storage of canopy water content within branches and leaves during the dry season, supporting our conclusion. A large part (r(2) = 0.75) of the variance in observed monthly midday fluorescence from GOSAT is explained by water stress over moderately stressed evergreen forests over Amazonia, which is reproduced by model simulations that include a full physiological representation of photosynthesis and fluorescence. The strong relationship between GOSAT and model fluorescence (r(2) = 0.79) was obtained using a fixed leaf area index, indicating that GPP changes are more related to environmental conditions than chlorophyll contents. When the dry season extended to drought in 2010 over Amazonia, midday basin-wide GPP was reduced by 15 per cent compared with 2009.