Solar-induced Chlorophyll Fluorescence Retrieval Research Articles

Mitigating the directional retrieval error of solar-induced chlorophyll fluorescence in the red band

Solar-induced chlorophyll fluorescence (SIF) is a promising tool to estimate gross primary production (GPP), but the retrieval of SIF is commonly noisy and highly sensitive to various interference factors. Particularly, the retrieval of SIF in the red band (RSIF) is more challenging than in the far-red SIF (FRSIF) due to the weaker fluorescence signal and the weaker absorption depth of oxygen at the red band compared with the far-red band. A comprehensive evaluation of all factors will allow a reproducible interpretation of SIF signals and advance the estimation of GPP from SIF. Recent studies have assessed the sensitivity of SIF retrieval to sensor characteristics, retrieval methods, and hardware specifications. However, none of these studies have systematically investigated the directional retrieval error of SIF resulting from the mismatch between irradiance measured above the canopy and the true irradiance reaching the canopy components viewed by a sensor. This study illustrated the effect of mismatched irradiance on the retrieval of RSIF using the commonly used standard 3FLD method based on SCOPE model simulations. The retrieval accuracy was highest in the hotspot direction, but it decreased as the observation direction was away from the hotspot. The relative root mean square error (RRMSE) was generally higher than 20 % in the forward directions. To reduce the retrieval error due to the mismatch effect, we proposed a modified 3FLD method (MFLD) by calculating the true irradiance reaching the canopy in a given direction based on geometric optical theory. The results showed that MFLD clearly improved the retrieval accuracy for RSIF, especially in the forward directions where RRMSE decreased by 10 % in most cases. For example, the RRMSE was reduced from 19.26 % to 5.50 % after mitigating the mismatch between the measured and actual solar irradiance, when the solar zenith angle was 40° and viewing zenith angle was 30° in the forward solar principal plane. Even at the nadir observation, the RRMSE was also reduced from 12.84 % to 5.64 %. In summary, MFLD can effectively mitigate the irradiance mismatch effect on the retrieval of RSIF. These results will improve our interpretation of the relationship between GPP and RSIF at different observation directions.

A SIF-based approach for quantifying canopy photosynthesis by simulating the fraction of open PSII reaction centers (qL)

Advances in retrieval of solar-induced chlorophyll fluorescence (SIF) provide a promising and independent approach for quantifying gross primary production (GPP) across spatial scales. Recent studies have highlighted the prominent role of qL, the fraction of open Photosystem II (PSII) reaction centers, in mechanistically modeling GPP from remote sensing SIF. However, due to the limited availability of simulated and experimental data, a comprehensive understanding of qL responses to environmental and physiological variations has yet to emerge, and as a consequence, prediction of qL across leaf and canopy scales is still in an early stage. Based on a global sensitivity analysis of a recently developed mechanical model of photosynthesis, we find that the broadband total SIF emitted from PSII (SIFTOT_FULL_PSII) and leaf temperature (TLeaf) are the two major predictors of qL. A leaf-level instrument is designed to obtain concurrent measurements of qL, SIFTOT_FULL_PSII, and TLeaf over a wide range of environmental conditions. From these measurements, we show that qL can be modelled as a hyperbolic function of SIFTOT_FULL_PSII with only one temperature-related parameter m which increases with temperature, but decreases rapidly as temperatures exceed the optimum temperature. It is suggested that m can be mathematically modelled by a peaked function. The results of the leaf-level experiments on winter wheat demonstrate that the proposed model predicts qL with high accuracy (R2 ≥ 0.91, rRMSE ≤ 8.46%) under diverse light and temperature conditions. The essential steps necessary to apply it at canopy scale, including estimating the escape fraction, removing fluorescence emitted from Photosystem I, and reconstructing SIFTOT_FULL_PSII from top-of-canopy (TOC) narrowband SIF, are also presented. Our results confirm that estimated GPP using SIF-informed qL agrees well with measured GPP at a winter wheat site (R2 = 0.81, rRMSE = 12.03%). The key benefit of SIF-informed approach is that SIFTOT_FULL_PSII provides critical information on the collective influence of the sub-canopy light environment on qL, avoiding the requirement to explicitly estimate qL at different canopy depths, potentially promoting the ability of SIF to mechanistically quantify photosynthetic CO2 assimilation at large scales.

Global retrieval of the spectrum of terrestrial chlorophyll fluorescence: First results with TROPOMI

Solar-Induced chlorophyll Fluorescence (SIF) could be used as an indicator of photosynthetic status due to the close relationship between SIF and the photosynthetic apparatus. Terrestrial SIF is emitted throughout the red and near-infrared spectrum and is characterized by two peaks centered around 685 nm and 740 nm, respectively. In this study, we present a data-driven approach to reconstruct the terrestrial SIF spectrum from measurements by TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 precursor mission. This approach makes use of solar Fraunhofer lines in the combined spectral windows devoid of strong atmospheric absorption features to retrieve SIF signal from the solar radiation reflected by the surface and atmosphere system. Information contents are mainly from the two windows close to the red and far-red SIF peaks, 663–686 nm and 743–758 nm. A linear forward model represented as an addition of the SIF-free radiance spectrum and the SIF component is proposed with a proper selection of its parameter settings. The SIF component was simulated as linear combinations of 2 basis SIF spectra. Through inverting the linear forward model, the SIF spectrum was retrieved from the solar radiation reflected by the surface and atmosphere system. The evaluation of the retrieval results is performed by inter-comparison with other SIF datasets. The comparisons display similar spatial distributions for the weekly global SIF composites for the first two weeks in June and December of 2019 and July and December of 2021. Especially the comparison of the far-red SIF datasets with other dedicated far-red SIF retrievals demonstrates close agreement, indicating consistency among the retrieval approaches. The reconstructed TROPOMI red SIF shows improved and more reasonable spatiotemporal distributions. The retrieval uncertainty for the weekly global composite is about 12% and 2% of the peak red and far-red SIF values, respectively, which can be considered as satisfactory error thresholds for global composites of SIF observations. Different spectral features for several typical biomes from reconstructed SIF spectra suggest that red and far-red SIF may carry complementary information on photosynthetic function and biophysical properties of the plant. For the first time, the reconstruction of the SIF spectrum is achieved for spaceborne measurements with the potential to open new applications for better understanding of the ecosystem function.

Combining Solar-Induced Chlorophyll Fluorescence and Optical Vegetation Indices to Better Understand Plant Phenological Responses to Global Change

Recent advances in the satellite retrieval of solar-induced chlorophyll fluorescence (SIF) provide new opportunities for understanding the phenological responses of ecosystems to global climate change. Because of the strong link between SIF and plant gross photosynthesis, phenological events derived from SIF represent the seasonal variation of ecosystem functioning (photosynthetic phenology) and differ from phenologies derived from traditional vegetation indices. We provide an overview of recent advances in remotely sensed photosynthetic phenologies, with a focus on their driving factors, their impact on the global carbon cycle, and their relationships with vegetation index-derived land surface phenology metrics. We also discuss future research directions on how to better use various phenological metrics to understand the responses of plants to global change.

Sensitivity of solar-induced fluorescence to spectral stray light in high resolution imaging spectroscopy

Remote sensing of solar-induced chlorophyll fluorescence (SIF) advances our ability to monitor gross primary productivity. Because SIF is usually <5% of recorded canopy radiance, sources of measurement error must be reduced for accurate SIF retrieval. Here we quantify the impact of spectral stray light on SIF retrieval using a high-resolution imaging spectrometer. We first derived the FLD retrieval solution in the presence of stray light under the simplifying assumptions that SIF, reflectance, and stray light are constant across the region of the spectrum used in the retrieval. We show that stray light contributions from the canopy and reference spectra could cancel out if obtained from the same instrument. In practice however, the simplifying assumptions are unlikely to hold because SIF and reflectance vary across regions of the spectrum commonly exploited by the FLD retrieval, and stray light can also vary across the spectrum, as we demonstrate with an empirical example. To quantify the impact of spectral stray light on SIF retrievals in more realistic scenarios, we performed a sensitivity analysis. We used a stray light signal distribution function and measurements of spectral radiance and SIF to generate spectra with known quantities of SIF and stray light over four orders of magnitude of stray light. We then quantified the bias in retrieved SIF using four SIF retrieval approaches—standard FLD, 3FLD, a spectral fitting method (SFM), and a method based on singular value decomposition (SVD)—applied to the red and/or far-red spectral domains. We found that spectral stray light can cause either a positive or negative bias in SIF estimates. In the highest stray light scenario, with spectral stray light one order of magnitude smaller than the radiance signal, the stray light error ranged from < ± 1% of SIF (for O2-A band retrievals with FLD, 3FLD, and SFM methods, and for far-red retrievals in the 748 nm to 756 nm domain with SVD-based and 3FLD methods applied to Fraunhofer lines) to >30% of SIF (O2-B band retrieval with SFM, and 3FLD applied to Fraunhofer lines in the red domain). For context, a bias of 27% of SIF is a comparable magnitude to seasonal variation in SIF observed in the Amazon basin, and to SIF differences among plant functional types. However, when spectral stray light was three orders of magnitude smaller than the radiance signal, mean bias was < ± 2% for all retrieval methods. Our analysis informs when spectral stray light corrections must be performed for SIF remote sensing.

HyScreen: A Ground-Based Imaging System for High-Resolution Red and Far-Red Solar-Induced Chlorophyll Fluorescence

Solar-induced chlorophyll fluorescence (SIF) is used as a proxy of photosynthetic efficiency. However, interpreting top-of-canopy (TOC) SIF in relation to photosynthesis remains challenging due to the distortion introduced by the canopy's structural effects (i.e., fluorescence re-absorption, sunlit-shaded leaves, etc.) and sun-canopy-sensor geometry (i.e., direct radiation infilling). Therefore, ground-based, high-spatial-resolution data sets are needed to characterize the described effects and to be able to downscale TOC SIF to the leafs where the photosynthetic processes are taking place. We herein introduce HyScreen, a ground-based push-broom hyperspectral imaging system designed to measure red (F687) and far-red (F760) SIF and vegetation indices from TOC with single-leaf spatial resolution. This paper presents measurement protocols, the data processing chain and a case study of SIF retrieval. Raw data from two imaging sensors were processed to top-of-canopy radiance by dark-current correction, radiometric calibration, and empirical line correction. In the next step, the improved Fraunhofer line descrimination (iFLD) and spectral-fitting method (SFM) were used for SIF retrieval, and vegetation indices were calculated. With the developed protocol and data processing chain, we estimated a signal-to-noise ratio (SNR) between 50 and 200 from reference panels with reflectance from 5% to 95% and noise equivalent radiance (NER) of 0.04 (5%) to 0.18 (95%) mW m-2 sr-1 nm-1. The results from the case study showed that non-vegetation targets had SIF values close to 0 mW m-2 sr-1 nm-1, whereas vegetation targets had a mean F687 of 1.13 and F760 of 1.96 mW m-2 sr-1 nm-1 from the SFM method. HyScreen showed good performance for SIF retrievals at both F687 and F760; nevertheless, we recommend further adaptations to correct for the effects of noise, varying illumination and sensor optics. In conclusion, due to its high spatial resolution, Hyscreen is a promising tool for investigating the relationship between leafs and TOC SIF as well as their relationship with plants' photosynthetic capacity.

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. In this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O2A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

A precise method unaffected by atmospheric reabsorption for ground-based retrieval of red and far-red sun-induced chlorophyll fluorescence

Remote sensing employs solar-induced chlorophyll fluorescence (SIF) as a proxy for photosynthesis from field to airborne and satellite sensors. The investigation of SIF offers a unique way of studying vegetation functioning from the local to the global scale. However, the passive, optical retrieval of the SIF signal is still challenging. Common retrieval approaches extract the SIF infilling directly from atmospheric oxygen bands in down-welling and up-welling radiance. They often involve a complex signal correction to compensate for atmospheric reabsorption and require long computing time. In contrast, the exploitation of solar Fraunhofer lines is devoid of atmospheric disturbances. We propose a new retrieval method for red and far-red SIF directly from up-welling radiance spectra in the spectral range between 650 nm and 810 nm by applying Partial Least Squares (PLS) regression machine learning. Solar Fraunhofer lines are exploited for SIF retrieval with the PLS approach by excluding telluric absorption features. The PLS models are trained and tested on synthetic reflectance and SIF data modeled with SCOPE. We identified a logarithmic relationship of the retrieval error with respect to signal-to-noise ratio of the instrument. The approach has been tested with real-world data measured by the Fluorescence Box (FloX), and evaluated against two well-established retrieval methods: the spectral fitting method (SFM) and the singular value decomposition (SVD). PLS models exploiting solar Fraunhofer lines retrieved meaningful SIF values with high precision and demonstrated robustness against atmospheric reabsorption, including from a 100m tall tower. In addition, PLS retrieval requires no complex correction for atmospheric reabsorption and computes 37 times faster than SFM. Hence, PLS retrieval allows fast and robust exploitation of SIF from solar Fraunhofer lines with high precision under conditions in which other retrieval approaches require complex atmospheric correction.

Simulation of solar-induced chlorophyll fluorescence by modeling radiative coupling between vegetation and atmosphere with WPS

Recent advances in instruments and retrieval methods enable measurements of solar-induced chlorophyll fluorescence (SIF) across a wide range of scales. Radiative transfer (RT) models for simulating scattering and (re-)absorption of SIF provide a powerful tool to study the upscaling of SIF signal from leaf level to terrestrial ecosystems. Based on the Monte Carlo ray-tracing (MCRT) model, WPS (Weighted Photon Spread), we made major extensions with new functionalities and systematic evaluation of the new modules. By modeling the radiative coupling between atmosphere and land surface with the same MCRT method, the non-fluorescent and SIF radiance received by sensors can be simulated at levels from top-of canopy to top-of-atmosphere (TOA) in a coherent manner. New extension to represent the three-dimensional (3-D) canopies with geometrical primitives composed of turbid medium makes the hyperspectral simulation (especially SIF) for a sensor with medium spatial resolution at kilometer-scale feasible and practical. Evaluations through ROMC (Radiation transfer model intercomparison Online Model Checker) show that the accuracy of the new module of 3-D structure representation in WPS is within 1% of the reference solution. The spectra of TOA radiance and SIF and their components simulated at nadir by WPS agree closely with those simulated by the coupled SCOPE and MODTRAN models with the coefficient of determination (R2) higher than 0.99 and the average absolute relative error (AARE) lower than 6.39%; for angular distributions of TOA radiance and SIF at 685 nm and 740 nm, R2 is higher than 0.81 and AARE is lower than 6.94%. Comparisons of the spectra of TOA radiance and SIF and their components simulated at nadir by WPS and the DART model give R2 higher than 0.99 and AARE lower than 3.5%; R2 is higher than 0.92 and AARE is lower than 5.92% for the TOA angular simulations. The WPS model was also evaluated by hyperspectral measurements through unmanned aerial vehicle at different altitudes, which shows that WPS can reproduce the spectral features of a rapeseed crop. WPS can be used as a versatile tool to assess the impacts of various factors on the SIF signal and to evaluate the SIF retrieval methods under different conditions.

Retrieval of solar-induced chlorophyll fluorescence (SIF) from satellite measurements: comparison of SIF between TanSat and OCO-2

Abstract. Solar-induced chlorophyll fluorescence (SIF) is emitted during photosynthesis in plant leaves. It constitutes a small additional offset to reflected radiance and can be observed by sensitive instruments with high signal-to-noise ratio and spectral resolution. The Chinese global carbon dioxide monitoring satellite (TanSat) acquires measurements of greenhouse gas column densities. The advanced technical characteristics of the Atmospheric Carbon-dioxide Grating Spectrometer (ACGS) onboard TanSat enable SIF retrievals from observations in the O2-A band. In this study, 1-year of SIF data was retrieved from Orbiting Carbon Observatory-2 (OCO-2) and TanSat measurements using the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing (IAPCAS)/SIF algorithm. A comparison between the IAPCAS/SIF results retrieved from OCO-2 spectra and the official OCO-2 SIF product (OCO2_Level 2_Lite_SIF.8r) shows a strong linear relationship (R2 &gt; 0.85) and suggests good reliability of the IAPCAS/SIF retrieval algorithm. Comparing global distributions of SIF retrieved by the IAPCAS/SIF from TanSat and OCO-2 shows the same spatial pattern for all seasons with a gridded SIF difference of less than 0.3 W m−2 µm−1 sr−1. The global distributions also agree well with the official OCO-2 SIF product with a difference of less than 0.2 W m−2 µm−1 sr−1. The retrieval uncertainty of seasonally gridded TanSat IAPCAS/SIF is less than 0.03 W m−2 µm−1 sr−1, whereas the uncertainty of each sounding ranges from 0.1 to 0.6 W m−2 µm−1 sr−1. The relationship between annually averaged SIF products and FLUXCOM gross primary productivity (GPP) was also estimated for six vegetation types in a 1∘ × 1∘ grid over the globe, indicating that the SIF data from the two satellites have the same potential in quantitatively characterizing ecosystem productivity. The spatiotemporal consistency between TanSat and OCO-2 and their comparable data quality enable joint usage of the two mission products. Data supplemented by TanSat observations are expected to contribute to the development of global SIF maps with more spatiotemporal detail, which will advance global research on vegetation photosynthesis.

Global GOSAT, OCO-2, and OCO-3 solar-induced chlorophyll fluorescence datasets

Abstract. The retrieval of solar-induced chlorophyll fluorescence (SIF) from space is a relatively new advance in Earth observation science, having only become feasible within the last decade. Interest in SIF data has grown exponentially, and the retrieval of SIF and the provision of SIF data products has become an important and formal component of spaceborne Earth observation missions. Here, we describe the global Level 2 SIF Lite data products for the Greenhouse Gases Observing Satellite (GOSAT), the Orbiting Carbon Observatory-2 (OCO-2), and Orbiting Carbon Observatory-3 (OCO-3) platforms, which are provided for each platform in daily netCDF files (Frankenberg, 2022, https://doi.org/10.22002/D1.8771; OCO-2 Science Team et al., 2020, https://doi.org/10.5067/XO2LBBNPO010; OCO-3 Science Team et al., 2020, https://doi.org/10.5067/NOD1DPPBCXSO). We also outline the methods used to retrieve SIF and estimate uncertainty, describe all the data fields, and provide users with the background information necessary for the proper use and interpretation of the data, such as considerations of retrieval noise, sun sensor geometry, the indirect relationship between SIF and photosynthesis, and differences among the three platforms and their respective data products. OCO-2 and OCO-3 have the highest spatial resolution of spaceborne SIF retrievals to date, and the target and snapshot area mode observation modes of OCO-2 and OCO-3 are unique. These modes provide hundreds to thousands of SIF retrievals at biologically diverse global target sites during a single overpass, and provide an opportunity to better inform our understanding of canopy-scale vegetation SIF emission across biomes.

Evaluation of SIF retrievals from narrow-band and sub-nanometer airborne hyperspectral imagers flown in tandem: Modelling and validation in the context of plant phenotyping

Solar-induced chlorophyll fluorescence (SIF) can be used as an indicator of crop photosynthetic activity and a proxy for vegetation stress in plant phenotyping and precision agriculture applications. SIF quantification is sensitive to the spectral resolution (SR), and its accurate retrieval requires sensors with sub-nanometer resolutions. However, for accurate SIF quantification from imaging sensors onboard airborne platforms, sub-nanometer imagers are costly and more difficult to operate than the commonly available narrow-band imagers (i.e., 4- to 6-nm bandwidths), which can also be installed on drones and lightweight aircraft. Although a few theoretical and experimental studies have evaluated narrow-band spectra for SIF quantification, there is a lack of research focused on comparing the effects of the SR on SIF from airborne hyperspectral imagers in practical applications. This study investigates the effects of SR and sensor altitude on SIF accuracy, comparing SIF quantified at the 760-nm O2-A band (SIF760) from two hyperspectral imagers with different spectral configurations (full width at half-maximum resolutions of 0.1–0.2 nm and 5.8 nm) flown in tandem on board an aircraft. SIF760 retrievals were compared from two different wheat and maize phenotyping trials grown under different nitrogen fertilizer application rates over the 2019–2021 growing seasons. SIF760 from the two sensors were correlated (R2 = 0.77–0.9, p < 0.01), with the narrow-band imager producing larger SIF760 estimates than the sub-nanometer imager (root mean square error (RMSE) 3.28–4.69 mW/m2/nm/sr). Ground-level SIF760 showed strong relationships with both sub-nanometer (R2 = 0.90, p < 0.001, RMSE = 0.07 mW/m2/nm/sr) and narrow-band (R2 = 0.88, p < 0.001, RMSE = 3.26 mW/m2/nm/sr) airborne retrievals. Simulation-based assessments of SIF760 for SRs ranging from 1 to 5.8 nm using the SCOPE model were consistent with experimental results showing significant relationships among SIF760 quantified at different SRs. Predictive algorithms of leaf nitrogen concentration using SIF760 from either the narrow-band or sub-nanometer sensor yielded similar performance, supporting the use of narrow-band resolution imagery for assessing the spatial variability of SIF in plant phenotyping, vegetation stress detection and precision agriculture contexts.

Prospects for Solar-Induced Chlorophyll Fluorescence Remote Sensing from the SIFIS Payload Onboard the TECIS-1 Satellite

The importance of solar-induced chlorophyll fluorescence (SIF) to monitoring vegetation photosynthesis has attracted much attention from the ecological and remote sensing research communities. Space-borne SIF products have been obtained owing to the rapid development of atmospheric satellites in recent years. The SIF Imaging Spectrometer (SIFIS) is a payload onboard the upcoming Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1) that is specifically designed for SIF monitoring. We conducted an in situ experiment to evaluate the performance of SIFIS on spectral measurement and SIF retrieval through comparison to the commercial spectrometer QE Pro. Disregarding the spatiotemporal mismatch between the collected measurements of the two spectrometers, the radiance spectra obtained synchronously by SIFIS and QE Pro showed a high level of consistency. The SIF retrieval, normalized difference vegetation index (NDVI), and near-infrared radiance of vegetation (NIRvR) results for a push-broom image shows consistent spatial distributions over both vegetated and nonvegetated surfaces. A quantitative comparison was conducted by strictly filtering matching pixels. For the far-red band, a high correlation was obtained between the SIF retrieval performances of SIFIS and QE Pro with R 2 = 0.70 and RMSE = 0.30 mW m − 2 s r − − 1 n m − 1 . However, a relatively poor correlation was observed for the red band with an R 2 value of 0.23 and an RMSE of 0.26 mWm −2 sr -−1 nm −1 . Despite the large uncertainties associated with this experiment, the results indicate that TECIS-1 should offer a reliable SIF monitoring performance after its launch.

Retrieval of Red Solar-Induced Chlorophyll Fluorescence With TROPOMI on the Sentinel-5 Precursor Mission

Solar-Induced chlorophyll Fluorescence (SIF) retrieved from spaceborne hyperspectral measurements can provide a synoptic perspective on the functioning of photosynthetic active vegetation and algae. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 precursor mission provides data for the retrieval of SIF with an unprecedented resolution in the spatial and temporal dimensions. In this study, we propose an approach for the retrieval of the red SIF peak value (at around 685 nm) over both land and ocean from TROPOMI measurements. This approach exploits the solar Fraunhofer lines located in the spectral window of 669–686 nm to disentangle SIF from the solar radiation reflected by the surface–atmosphere system. First, through simulated TROPOMI-like datasets, we determine the proper parameter settings and demonstrate the feasibility of the approach for the red SIF retrieval from TROPOMI data. Then, the approach is applied to real TROPOMI measurements. The red SIF retrieved with the proposed approach for two months’ TROPOMI data is compared with another TROPOMI red SIF dataset and the marine normalized fluorescence line height (nFLH) product of the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). The comparisons display similar spatial distributions over both land and ocean for the weekly global composites. Especially, the comparison of the two red SIF datasets demonstrates good agreement overall, indicating consistency of the two retrieval approaches. The retrieval uncertainty for the weekly global composite is about 13% and 10% of the peak SIF value over land/ocean, respectively, which can be considered as satisfactory error thresholds for global SIF observations.

Mineral Luminescence Observed From Space

AbstractMethods developed to explore the luminescent properties of the moon facilitated the development of techniques to infer terrestrial solar‐induced chlorophyll fluorescence (SIF) from satellite instruments. While single SIF retrievals are inherently noisy, averaging many retrievals allows us to obtain highly accurate estimates. We analyzed several years of aggregated SIF data collected by the TROPOspheric Monitoring Instrument (TROPOMI) and the Orbiting Carbon Observatory‐2 (OCO‐2) over nonvegetated areas to explore the potential of SIF retrievals beyond the realm of photosynthesis. The fundamentally different retrievals at varying wavelengths in the near‐infrared reveal that about 10% of all barren surfaces are weakly luminescent, while a few areas luminesce strongly—amounts comparable to SIF from vegetation. By means of lithological maps, we attributed the strongest luminescence signals to exposed carbonate sedimentary rocks. Besides a detailed evaluation of the signal properties, we discussed implications for SIF data sets and other remote sensing products.

Solar-induced chlorophyll fluorescence from the Geostationary Carbon Cycle Observatory (GeoCarb): An extensive simulation study

The Geostationary Carbon Cycle Observatory (GeoCarb), to be launched in 2023, will be capable of measuring solar-induced chlorophyll fluorescence (SIF) and add to the current space-based record which started in 1995. GeoCarb will be unique as it will be the first geostationary satellite capable of sensing SIF over the American continents. Consequently, SIF measurements from GeoCarb can be performed much more flexibly compared to polar-orbiting platforms. With its scan mirror assembly, the instrument can point to any location on the Earth disc. This will allow measurements to be collected at various times of day, and measurement locations can be re-visited several times within a day. In expectation of the launch, we conduct an extensive, SIF-focused simulation study and explore the capability and limitations of the instrument and its particular sampling approach. Using cloud information from real measurements, as well as other observation- and model-based data, we produce over four million atmospheric simulations of GeoCarb measurements that the instrument would see throughout a full day. We then apply dedicated SIF retrieval algorithms on the simulated spectra and investigate the results along with cloud-screening performance and emergent retrieval biases and subsequent bias correction. Finally, we make comparisons with currently operating instruments where appropriate and show future science users of GeoCarb SIF what a typical day of measurements will yield.

The Effect of Principal Component Analysis Parameters on Solar-Induced Chlorophyll Fluorescence Signal Extraction

Solar-induced chlorophyll fluorescence (SIF), one of the three main releasing pathways of vegetation-absorbed photosynthetic active radiation, has been proven as an effective monitoring implementation of leaf photosynthesis, canopy growth, and ecological diversity. There exist three categories of SIF retrieval methods, and the principal component analysis (PCA) retrieval method is obtrusively eye-catching due to its brief, data-driven characteristics. However, we still lack a lucid understanding of PCA’s parameter settings. In this study, we examined if principal component numbers and retrieval band regions could have effects on the accuracy of SIF inversion under two controlled experiments. The results revealed that the near-infrared region could remarkably boost SIF’s retrieval accuracy, whereas red and near-infrared bands caused anomalous values, which subverted a traditional view that more retrieval regions might provide more photosynthetic information. Furthermore, the results demonstrated that three principal components would benefit more in PCA-based SIF retrieval. These arguments further help elucidate the more in-depth influence of the parameters on the PCA retrieval method, which unveil the potential effects of different parameters and give a parameter-setting foundation for the PCA retrieval method, in addition to assisting retrieval achievements.

Instrumentation sensitivities for tower-based solar-induced fluorescence measurements

Solar-induced chlorophyll fluorescence (SIF) has been widely cited as a proxy for photosynthesis and is being incorporated as a common input in terrestrial primary productivity models. Though satellite-based SIF products show close relationships with terrestrial gross primary productivity (GPP), there is wide variability in the magnitude of published SIF retrievals made at intermediate scales. In a meta-analysis of the tower-based and airborne SIF literature, we found that mean SIF retrievals from unstressed vegetation spanned a wide range, from 0.041 mW m−2 nm−1 sr−1 to 14.8 mW m−2 nm−1 sr−1, with a majority of values falling below 4 mW m−2 nm−1 sr−1. We compiled information on reported spectrometer calibration procedures, hardware characterizations, and associated corrections from these same papers, and found inconsistent reporting on if and how key calibration methodology was performed. In order to quantify the importance of such methodological differences on final SIF retrievals made at a proximal scale, we performed radiometric calibrations and corrections for electronic dark current, detector noise, atmospheric O2 absorbance, and cosine corrector effects on three field-deployed spectrometers. We found dramatic changes in SIF retrieval magnitude before and after applying calibrations and corrections, as well as significant differences between instrument performance in the field and expected performance based on laboratory characterizations. Based on these tests, and on a Monte Carlo simulation of uncertainty estimates associated with each of these corrections, it is likely that calibration methodologies and hardware characterizations explain some of the observed variability in published SIF retrievals. This wide range in baseline SIF retrieval methodologies and resultant magnitudes severely limit researchers' ability to synthesize and advance the utility of SIF in modeling GPP across scales. Further, variability in calibration and correction methodology may explain the weak SIF-GPP relationship across studies at tower scales.

OCO-3 early mission operations and initial (vEarly) XCO2 and SIF retrievals

NASA's Orbiting Carbon Observatory-3 (OCO-3) was installed on the International Space Station (ISS) on 10 May 2019. OCO-3 combines the flight spare spectrometer from the Orbiting Carbon Observatory-2 (OCO-2) mission, which has been in operation since 2014, with a new Pointing Mirror Assembly (PMA) that facilitates observations of non-nadir targets from the nadir-oriented ISS platform. The PMA is a new feature of OCO-3, which is being used to collect data in all science modes, including nadir (ND), sun-glint (GL), target (TG), and the new snapshot area mapping (SAM) mode.This work provides an initial assessment of the OCO-3 instrument and algorithm performance, highlighting results from the first 8 months of operations spanning August 2019 through March 2020. During the In-Orbit Checkout (IOC) phase, critical systems such as power and cooling were verified, after which the OCO-3 spectrometer and PMA were subjected to a series of rigorous tests. First light of the OCO-3 spectrometer was on 26 June 2019, with full science operations beginning on 6 August 2019. The OCO-3 spectrometer on-orbit performance is consistent with that seen during preflight testing. Signal to noise ratios are in the expected range needed for high quality retrievals of the column-averaged carbon dioxide (CO2) dry-air mole fraction (XCO2) and solar-induced chlorophyll fluorescence (SIF), which will be used to help quantify and constrain the global carbon cycle.The first public release of OCO-3 Level 2 (L2) data products, called “vEarly”, is being distributed by NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC). The intent of the vEarly product is to evaluate early mission performance, facilitate comparisons with OCO-2 products, and identify key areas to improve for the next data release. The vEarly XCO2 exhibits a root-mean-squared-error (RMSE) of ≃ 1, 1, 2 ppm versus a truth proxy for nadir-land, TG&SAM, and glint-water observations, respectively. The vEarly SIF shows a correlation with OCO-2 measurements of >0.9 for highly coincident soundings. Overall, the Level 2 SIF and XCO2 products look very promising, with performance comparable to OCO-2. A follow-on version of the OCO-3 L2 product containing a number of refinements, e.g., instrument calibration, pointing accuracy, and retrieval algorithm tuning, is anticipated by early in 2021.

NEW SOLAR-INDUCED CHLOROPHYLL FLUORESCENCE RETRIEVAL ALGORITHM BASED ON TANSAT SATELLITE DATA

Abstract. Solar-induced chlorophyll fluorescence (SIF) is an indicator of plant photosynthesis which could be detected by satellite. However，some existing algorithms are easily affected by the inaccuracy of satellite data which will causing deviation in the retrieval of SIF. To avoid "outliers" with inaccuracy affecting the retrieval results, a random sample consensus algorithm (RANSAC) was introduced to retrieve SIF in this paper. The results show that the chlorophyll fluorescence value obtained by this method is consistent with the OCO-2 SIF product (R2 = 0.81), and also consistent with the MODIS vegetation index (R2 = 0.87 with NDVI, R2 = 0.85 with EVI). Compared with the existing SIF products (OCO-2 SIF), the SIF retrieved in this paper was better in spatial details and outlier distribution.