Sun-Induced chlorophyll Fluorescence (SIF) is the most promising remote-sensing proxy of Gross Primary Production (GPP) in terrestrial ecosystems. However, the estimation of GPP using SIF is challenging when plants experience stress, particularly during extreme climatic events whose frequency is projected to increase in the future. Recently, the feasibility of canopy-level active chlorophyll fluorescence measurements (LED-induced chlorophyll fluorescence), which directly measure the apparent fluorescence yield (FyieldLIF), has provided new perspectives on detecting the responses of plants to stress. This study was conducted during the summer 2022 European heat waves in a mixed temperate deciduous broadleaf forest, located in the French Fontainebleau-Barbeau station. Continuous measurements of carbon dioxide (CO2) and energy exchanges, SIF, FyieldLIF, and ancillary environmental variables were acquired. We investigated how heat-wave induced high atmospheric dryness, measured as Vapor Pressure Deficit, affected canopy chlorophyll fluorescence (both SIF and FyieldLIF) and GPP, as well as their relationships. At the half-hourly scale, our results revealed a decrease of the correlation between SIF and GPP (R2 decreased from 0.49 to 0.17) at high atmospheric dryness. In contrast, the correlation between FyieldLIF and GPP increased significantly under high atmospheric dryness (R2 increased from 0.07 to 0.43). However, at the daily scale, the correlations between SIF and GPP and between FyieldLIF and GPP showed an overall increase compared to the half-hourly scale, suggesting a time-scale-dependent response of these relationships to atmospheric dryness. This study also highlighted FyieldLIF's advantage in detecting plant responses

Solar-induced chlorophyll fluorescence (SIF) is a subtle but informative probe of plant photosynthesis. Quantifying the three-dimensional (3D) distribution of SIF benefits a better understanding of photosynthesis variations over heterogeneous canopies. Although radiative transfer models (RTMs) provide a solid theoretical basis for simulating the 3D SIF distribution, most RTMs use virtual scenes with complex reconstruction processes. This study aims to develop a 3D SIF simulation model (FluorLiDAR) directly driven by terrestrial light detection and ranging (LiDAR) data using leaf and canopy RTMs, including a 3D PAR (photosynthetically active radiation) simulation model, the Fluspect model, the atmosphere radiative transfer module in SCOPE, , and the multiple scattering coefficients of sunlit and shaded leaves from the 4-scale model. The results show that (1) the simulated and measured SIF patterns were consistent, with R2 2 (RMSE) values of 0.73 (0.17 mW/nm/m2/sr) 2 /sr) and 0.76 (0.12 mW/nm/m2/sr) 2 /sr) for 1-min sampling and 10-min averages, respectively. Moreover, the R2 2 between FluorLiDAR and the DART simulation reached 0.94. The R2 2 of FluorLiDAR and DART were both higher than 1D mSCOPE using every 10-min sampling data. (2) Point density, denoted by average NPD (nearest point distance), influenced the performance of our model mainly when it was smaller than 0.1 m. Chlorophyll content had less influence on the model accuracy (R2 2 and rRMSE), and the bias between simulation and measurement decreased as chlorophyll content increased. (3) The simulated 3D SIF distribution pattern closely resembled PAR within the canopy. Besides, FluorLiDAR can simulate the hot spot effect like DART and mSCOPE though the effect was not as obvious as the other two models. This study highlights the potential of a LiDAR-driven SIF model for 3D SIF simulation over a heterogeneous canopy, which may benefit the understanding of the structural impacts on forest photosynthesis in real forest scenes.

æ¤ç‰©å ‰åˆä½œç”¨æ‰€æä¾›çš„ç‰©è´¨å’Œèƒ½é‡æ˜¯äººç±»èµ–ä»¥ç”Ÿå­˜çš„å ³é”®å› ç´ ï¼Œè€Œæ—¥å ‰è¯±å¯¼å¶ç»¿ç´ è§å ‰SIF（Sun-Induced chlorophyll Fluorescenceï¼‰æ˜¯æ¤ç‰©å ‰åˆä½œç”¨çš„å‰¯äº§å“ï¼Œä¸Žå ‰åˆä½œç”¨å ³ç³»å¯†åˆ‡ï¼Œæ·±å ¥ç ”ç©¶SIFå°†å¯¹äºŽæ›´åŠ æ·±å ¥ç†è§£å ‰åˆä½œç”¨æœºåˆ¶æœ‰ç€é‡è¦çš„æ„ä¹‰ã€‚ç›®å‰ï¼Œè¿‘åœ°é¢æ¤è¢«å† å±‚SIFé¥æ„Ÿè§‚æµ‹å‘å±•è¿ é€Ÿï¼Œä½†ä¸åŒSIF观测系统间差异较大。本文通过比较分析不同塔基SIFè§‚æµ‹ç³»ç»ŸåŠå ¶ç‰¹å¾ï¼Œå½’çº³äº†å¡”åŸºSIF观测方式和方法，提出了塔基SIF观测技术规范。塔基SIFè§‚æµ‹ä¸»è¦æœ‰ä¸¤å°å ‰è°±ä»ªå’Œä¸€å°å ‰è°±ä»ªç»“åˆå ‰è·¯åˆ‡æ¢å¼€å ³çš„è§‚æµ‹æ–¹æ³•ï¼Œå¯ä»¥é‡‡å–åŒåŠçƒå’ŒåŠçƒâ€”é”¥ä½“ä¸¤ç§è§‚æµ‹æ–¹å¼ã€‚SIFprismç³»ç»Ÿæ˜¯ä¸€ç§æ–°çš„åŸºäºŽå ‰å­¦æ£±é•œçš„SIF自动观测系统，本文介绍了SIFprismç³»ç»Ÿè½¯ç¡¬ä»¶ç»„æˆå’Œå ‰è°±æ•°æ®é‡‡é›†æµç¨‹ï¼Œå¹¶ä»¥SIFprismç³»ç»Ÿä¸ºä¾‹é˜è¿°äº†å¡”åŸºè§‚æµ‹ç³»ç»Ÿå ‰è°±æ•°æ®å¤„ç†æµç¨‹ï¼Œåˆ†æžäº†SIF反演过程可能存在的不确定性，最后对近地面SIF观测进行了展望。

Solar‐induced chlorophyll fluorescence (SIF) provides remotely sensible signals for monitoring gross primary production (GPP). Ground‐based multiangle observations of both red and far‐red SIF above wheat and maize canopies were conducted to examine angular effects on SIF. With these new measurements, we were able for the first time to refine and apply an algorithm developed for angular normalization of both red and far‐red SIF measurements. The angular normalization improved the correlation of SIF with GPP derived from eddy covariance measurements at the instantaneous scale (1 min), with increases of the diurnal coefficients of determination (of sunlit SIF with GPP) up to 0.21 for far‐red SIF and 0.3 for red SIF based on analysis on 6 sunny days. The improvement was slightly smaller for far‐red SIF than for red SIF, attributing to that the observed angular variation of SIF in the red band was greater than that in the far‐red band due to weaker multiple scattering in the red band in the canopy. In addition, at the hourly time scale, far‐red sunlit SIF shows its advantage to track GPP for heterogonous canopies, while angular normalization of red SIF is effective for homogeneous canopies. In comparison with another angular normalization method based on the escape ratio using datasets over both wheat and maize canopies, the two kinds of method show similar ability to improve the correlation between SIF and GPP, while the results suggest a limitation of SIF in estimating GPP for dense canopies where the fraction of shaded leaves are large.

Photosynthetic capacity (leaf maximum carboxylation rate, V-cmax) 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 V-cmax at the ecosystem level. However, the relationship between SIF and V-cmax at the leaf and canopy levels is still poorly understood. In this study, we investigated the dynamic relationship between SIF and V-cmax 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 V-cmax during the growing season, although the relationship varied with plant growth stages. After flowering, SIFy showed a stronger relationship with V-cmax than SIF flux at both the leaf and canopy levels. Further analysis suggested that the divergence of the link between SIF and V-cmax 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 V-cmax at the leaf and canopy levels.

The accurate retrieval of forest functional and structural parameters is of great significance in the scientific research of ecosystem, global change, and carbon and nitrogen cycles. Recently, an unmanned aerial vehicle (UAV) hyperspectral imaging system provides a cost-effective way to capture the hyperspectral imageries from any points of the hemisphere above a forest canopy. However, compared with single-angle hyperspectral images, the multiangle hyperspectral images provide more information about forest functional and structural characteristics. We developed a semiautomatic multiangle observation method using a UAV hyperspectral imaging system and successfully collected the multiangle hyperspectral imageries with clear hotspots of broadleaf and coniferous forest canopies. Our results indicated that the hotspot of a forest canopy had a great effect on the reflectance, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) of forests. The maximum values of canopy reflectance and EVI were found at the hotspot position, while the minimum NDVI was at the hotspot. Moreover, the hotspot effect was similar in both broadleaf and coniferous forests. Although the hotspot had no obvious effects on the photochemical reflectance index (PRI), different view zenith angles had a great effect on PRI. Our findings provide a solid foundation for retrieving forest structural parameters using fully automatic multiangle hyperspectral imaging system at both aerial and satellite platforms. (C) 2020 Society of Photo Optical Instrumentation Engineers (SPIE)

Quantifying global photosynthesis remains a challenge due to a lack of accurate remote sensing proxies. Solar-induced chlorophyll fluorescence (SIF) has been shown to be a good indicator of photosynthetic activity across various spatial scales. However, a global and spatially challenging estimate of terrestrial gross primary production (GPP) based on satellite SIF remains unresolved due to the confounding effects of species-specific physical and physiological traits and external factors, such as canopy structure or photosynthetic pathway (C-3 or C-4). Here we analyze an ensemble of far-red SIF data from OCO-2 satellite and ground observations at multiple sites, using the spectral invariant theory to reduce the effects of canopy structure and to retrieve a structure-corrected total canopy SIF emission (SIFtotal). We find that the relationships between observed canopy-leaving SIF and ecosystem GPP vary significantly among biomes. In contrast, the relationships between SIFtotal and GPP converge around two unique models, one for C-3 and one for C-4 plants. We show that the two single empirical models can be used to globally scale satellite SIF observations to terrestrial GPP. We obtain an independent estimate of global terrestrial GPP of 129.56 +/- 6.54 PgC/year for the 2015-2017 period, which is consistent with the state-of-the-art data- and process-oriented models. The new GPP product shows improved sensitivity to previously undetected 'hotspots' of productivity, being able to resolve the double-peak in GPP due to rotational cropping systems. We suggest that the direct scheme to estimate GPP presented here, which is based on satellite SIF, may open up new possibilities to resolve the dynamics of global terrestrial GPP across space and time.

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) show the potential to estimate Vcmax at the ecosystem level. However, the SIF-Vcmax relationship at leaf and canopy levels are still poorly understood. This study investigates the relationship between leaf or canopy SIF and leaf Vcmax and its controlling factors based on SIF and CO2 response measurements in rice. The results show that SIF (or its yield, SIFy) and Vcmax are strongly correlated during the growing season, though the relationship varies with rice growth stages. After the flowering period, SIFy has a stronger relationship with Vcmax than SIF flux at both leaf and canopy levels. Further analysis suggests that changes in canopy structure and leaf physiology lead to the divergence of the link between SIF and Vcmax from leaf to canopy level. Our findings highlight the need to account for plant physiology and canopy structure in interpreting the SIF signal across spatial scales. Our observation-based results provide evidence that remotely sensed SIF observations can be used to track seasonal variations of Vcmax at the leaf and canopy levels.

Remote sensing of far-red sun-induced chlorophyll fluorescence (SIF) has emerged as an important tool for studying gross primary productivity (GPP) at the global scale. However, the relationship between SIF and GPP at the canopy scale lacks a clear mechanistic explanation. This is largely due to the poorly characterized role of the relative contributions from canopy structure and leaf physiology to the variability of the top-of-canopy, observed SIF signal. In particular, the effect of the canopy structure beyond light absorption is that only a fraction (fesc) of the SIF emitted from all leaves in the canopy can escape from the canopy due to the strong scattering of near-infrared radiation. We combined rice, wheat and corn canopy-level in-situ datasets to study how the physiological and structural components of SIF individually relate to measures of photosynthesis. At seasonal time scales, we found a considerably strong positive correlation (R2=0.4-0.6) of fesc to the seasonal dynamics of the photosynthetic light use efficiency (LUEp), while the estimated physiological SIF yield was almost entirely uncorrelated to LUEP both at seasonal and diurnal time scales, with the partial exception of wheat. Consistent with these findings, the canopy structure and radiation component of SIF, defined as the product of APAR and fesc, explained the relationship of observed SIF to GPP and even outperformed GPP estimation based on observed SIF at two of the three sites investigated. These results held for both half-hourly and daily mean values. In contrast, the total emitted SIF, obtained by normalizing observed SIF for fesc, improved only the relationship to APAR but considerably decreased the correlation to GPP for all three crops. Our findings demonstrate the dominant role of canopy structure in the SIF-GPP relationship and establish a strong, mechanistic link between the near-infrared reflectance of vegetation (NIRv) and the relevant canopy structure information contained in the SIF signal. These insights are expected to be useful in improving remote sensing based GPP estimates.

Satellite remotely sensed fraction of photosynthetically active radiation (FPAR) products are widely used in land-surface monitoring and modeling, especially for estimating global terrestrial photosynthetic activity through light use efficiency (LUE) models. PAR absorbed by active chlorophyll (APAR(chl)) is directly linked to vegetation photosynthesis and can be used to estimate ecosystem gross primary production (GPP). Previous studies have demonstrated that solar induced chlorophyll fluorescence has very tight relationship with APAR(chl) at various ecosystems. Therefore, the solar angle normalized SIF (nSIF) is directly related to the fraction of PAR absorbed by chlorophyll (FPAR(chl)). This paper intercompared six space FPAR products from Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), Copernicus Global Land Service (CGLS), Multi-angle Imaging SpectroRadiometer (MISR), Earth Polychromatic Imaging Camera (EPIC) and Ocean and Land Colour Instrument (OLCI). Their potential relationships with FPAR(chl) were indirectly evaluated with both spaceborne (Orbiting Carbon Observatory-2, OCO-2 and TROPOspheric Monitoring Instrument, TROPOMI) and airborne (Chlorophyll Fluorescence Imaging Spectrometer, CFIS) nSIF data as well as in situ GPP measurements. Our results show that these FPAR products are different in terms of amplitudes and seasonal variations across biomes. Among six FPAR products, OLCI FPAR shows the best relationships with TROPOMI nSIF740, OCO-2 nSIF757, and CFIS nSIF755. The coefficient of determination (R-2) for the relationship between OLCI FPAR and TROPOMI nSIF740 is 0.79 +/- 0.17 on a global average. APAR calculated from OLCI also exhibits the best relationship (R-2 = 0.79) with in situ GPP over 25 flux towers.

The photochemical reflectance index (PRI) has been suggested as an indicator of light use efficiency (LUE), and for use in the improvement of estimating gross primary production (GPP) in LUE models. Over the last two decades, solar-induced fluorescence (SIF) observations from remote sensing have been used to evaluate the distribution of GPP over a range of spatial and temporal scales. However, both PRI and SIF observations have been decoupled from photosynthesis under a variety of non-physiological factors, i.e., sun-view geometry and environmental variables. These observations are important for estimating GPP but rarely reported in the literature. In our study, multi-angle PRI and SIF observations were obtained during the 2018 growing season in a maize field. We evaluated a PRI-based LUE model for estimating GPP, and compared it with the direct estimation of GPP using concurrent SIF measurements. Our results showed that the observed PRI varied with view angles and that the averaged PRI from the multi-angle observations exhibited better performance than the single-angle observed PRI for estimating LUE. The PRI-based LUE model when compared to SIF, demonstrated a higher ability to capture the diurnal dynamics of GPP (the coefficient of determination (R-2) = 0.71) than the seasonal changes (R-2= 0.44), while the seasonal GPP variations were better estimated by SIF (R-2= 0.50). Based on random forest analyses, relative humidity (RH) was the most important driver affecting diurnal GPP estimation using the PRI-based LUE model. The SIF-based linear model was most influenced by photosynthetically active radiation (PAR). The SIF-based linear model did not perform as well as the PRI-based LUE model under most environmental conditions, the exception being clear days (the ratio of direct and diffuse sky radiance > 2). Our study confirms the utility of multi-angle PRI observations in the estimation of GPP in LUE models and suggests that the effects of changing environmental conditions should be taken into account for accurately estimating GPP with PRI and SIF observations.

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. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)

Gross primary production (GPP) from photosynthesis by terrestrial vegetation is the largest sink of atmospheric CO 2 . Sun-induced chlorophyll fluorescence (SIF) has been shown a powerful proxy for photosynthetic activity and used to estimate GPP. However, both non-physiological and functional factors controlling the emission of canopy SIF. The non-physiological factors, especially the sun-viewer geometry, impact the relationships between SIF and GPP. In this study, we did near-surface observations of both carbon flux and multi-view-angle spectra above a wheat canopy. The carbon flux was used to calculate GPP and the canopy spectra were used to retrieve SIF. SIF is significantly correlated with the angle between sun and viewer than SIF (R 2 =0.63). The relationships of SIF with GPP are also changing with different view azimuth angles. Generally, SIF observed at 180 o (pointing north) are more correlated to GPP than that at the other two angles. A model recently developed by He et al. (2017) was used to normalize multi-angle SIF to the hotspot direction (SIF h ) and to compute the canopy-level total SIF (SIF t ), in order to reduce the effects of sun-viewer geometry on SIF. Compared to the correlation of GPP with the original observed SIF (SIF obs ), the coefficients of determination (R 2 ) increase by ~0.1 and ~0.05 for those of GPP with SIF h and SIF t , respectively. These results would be helpful in estimating GPP of crops at large scales using remote sensing techniques.

During recent decades, solar-induced chlorophyll fluorescence (SIF) has shown to be a good proxy for gross primary production (GPP), promoting the development of ground-based SIF observation systems and supporting a greater understanding of the relationship between SIF and GPP. However, it is unclear whether such SIF-oriented observation systems built from different materials and of different configurations are able to acquire consistent SIF signals from the same target. In this study, we used four different observation systems to measure the same targets together in order to investigate whether SIF from different systems is comparable. Integration time (IT), reflectance, and SIF retrieved from different systems with hemispherical-conical (hemi-con) and bi-hemispherical (bi-hemi) configurations were also evaluated. A newly built prism system (SIFprism, using prism to collect both solar and target radiation) has the shortest IT and highest signal to noise ratio (SNR). Reflectance collected from the different systems showed small differences, and the diurnal patterns of both red and far-red SIF derived from different systems showed a marginal difference when measuring the homogeneous vegetation canopy (grassland). However, when the target is heterogeneous, e.g., the Epipremnum aureum canopy, the values and diurnal pattern of far-red SIF derived from systems with a bi-hemi configuration were obviously different with those derived from the system with hemi-con configuration. These results demonstrate that different SIF systems are able to acquire consistent SIF for landscapes with a homogeneous canopy. However, SIF retrieved from bi-hemi and hemi-con configurations may be distinctive when the target is a heterogeneous (or discontinuous) canopy due to the different fields of view and viewing geometries. Our findings suggest that the bi-hemi configuration has an advantage to measure heterogeneous canopies due to the large field of view for upwelling sensors being representative for the footprint of the eddy covariance flux measurements.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides great potential for estimating gross primary production (GPP) of terrestrial ecosystems. A strong relationship between SIF and GPP has been observed at the seasonal scale from both ground-based and satellite observations. However, variations of SIF due to changes in plant growth stages appear to influence the SIF-GPP relationship. It remains unclear how this relationship is affected by plant growth-related changes, especially for C4 plants such as maize. In this study, continuous in situ measurements for canopy far-red SIF retrieval and GPP calculation were made in maize during the growing season of 2017. Diurnal and seasonal variations of canopy SIF and its yield (SIFyield) were analyzed over different growth stages of maize to understand how they affect the relationship with GPP. The results show that the relationship between SIF and GPP varies with the growth stages of maize during the growing season, indicating that canopy structure has a strong impact on the seasonal variations of canopy SIF and its relation to GPP. Furthermore, we found that SIFyield is significantly correlated with canopy photosynthetic light use efficiency (LUE) at the canopy level throughout the season. However, it is almost uncorrelated with LUE after adjusting for the effects of canopy structure with the structural vegetation index MTVI2. This finding highlights the importance of canopy structure in the relationship between SIFyield and LUE, complicating the use of canopy SIF for tracking vegetation physiological activity. Overall, our observation-based findings show that canopy structure affects the SIF-GPP relationship, strengthening our understanding of the mechanistic link between SIF and photosynthesis.

Forest’s net primary productivity (NPP) is a key index in studying interactions of climate and vegetation, and accurate prediction of NPP is essential to understand the forests’ response to climate change. The magnitude and trends of forest NPP not only depend on climate factors (e.g., temperature and precipitation), but also on the succession stages (i.e., forest stand age). Although forest stand age plays a significant role on NPP, it is usually ignored by remote sensing-based models. In this study, we used remote sensing data and meteorological data to estimate forest NPP in China based on CASA model, and then employed field observations to inversely estimate the parameter of maximum light-use efficiency (εmax) of forests in different stand ages. We further developed functions to describe the relationship between maximum light-use efficiency (εmax) and forest stand age, and estimated forest age-dependent NPP based on these functions. The results showed that εmax has changed according to forest types and the forest stand age. For deciduous broadleaf forest, the average εmax of young, middle-aged and mature forest are 0.68, 0.65 and 0.60 gC MJ-1. For evergreen broadleaf forest, the average εmax of young, middle-aged and mature forests are 1.05, 1.01 and 0.99 gC MJ-1. For evergreen needleleaf forest, the average εmax of young, middle-aged and mature forests are 0.72, 0.57 and 0.52 gC MJ-1.The NPP of young and middle-aged forests were underestimated based on a constant εmax. Young forests and middle-aged forests had higher εmax, and they were more sensitive to trends and fluctuations of climate change, so they led to greater annual fluctuations of NPP. These findings confirm the importance of considering forest stand age to the estimation of NPP and they are significant to study the response of forests to climate change.