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The joint use of solar-induced chlorophyll fluorescence (SIF) and the photochemical reflectance index (PRI) has been shown to improve gross primary productivity (GPP) estimation across various plant functional types. However, the utility of PRI in combination with SIF for transpiration (T) estimation has not yet been explored. Additionally, current SIF-driven transpiration models including linear models, semi-mechanical models (combination of canopy conductance, g C , derived from a SIF and vapor pressure deficit, VPD, driven linear model with the Penman-Monteith model), and hybrid models (combination of g C derived from a SIF and VPD driven machine learning model with the Penman-Monteith model) have rarely been mutually assessed. Based on concurrent remotely sensed SIF and PRI, and eddy covariance flux measurements during one growing season for a winter wheat ecosystem in northern China, we investigated the mediating effect of PRI on SIF-driven T estimation under different VPD conditions and compared the performance of linear, semi-mechanical, and hybrid models in estimating T. Our results showed that the mediating effect of PRI on T described in the SIF-driven linear, semi-mechanistic, and hybrid models was significant under high VPD conditions rather than under low VPD conditions. Specifically, based on T partitioned using an underlying water use efficiency method as a benchmark, the root mean square error (RMSE) value of the PRI-mediated linear, semi-mechanistic, and hybrid models was 28.01 W/m2, 22.25 W/m2, and 28.71 W/m2 lower, respectively, than those of the corresponding models without PRI when VPD was >1.5 kPa. Based on T partitioned using a transpiration estimation algorithm as a benchmark, these three models also exhibited a significant reduction in RMSE under high VPD conditions after considering PRI. The main rationale behind the PRI improvement is that PRI can track photosynthetic dynamics under high VPD conditions. Based on the simulation results of the Soil-Canopy-Observation of Photosynthesis and Energy fluxes (SCOPE) model, PRI can serve as an indicator for non-photochemical quenching (NPQ) within this ecosystem. Consequently, PRI can enhance the capability of SIF to characterize the energy dissipation of photosynthetically active radiation and help SIF to yield more accurate information on GPP and g c under high VPD conditions. Finally, the order of model performance in estimating T was generally hybrid model > semi-mechanistic model > linear model. Our findings show the effectiveness of PRI for improving SIF-driven transpiration estimation under high VPD conditions and provide a new hybrid model for estimating T from SIF. • PRI can improve the ability of SIF to estimate T under high VPD conditions. • A hybrid model applies g c from a SIF driven machine learning model to P-M model. • Hybrid model can better estimate T than semi-mechanistic and empirical models. [ABSTRACT FROM AUTHOR]

• NDVI represents photosynthetic phenology only in deciduous trees. • Gcc tracks photosynthetic phenology more accurately than GRVI at the canopy scale. • ɸ NPQ and ɸ f,D have great influences on the spectral signal changes of NIRv and PRI. • Good consistency was found between NIRv and PRI for predicting A max. Vegetation photosynthetic phenology is an important indicator to characterize the biological responses of terrestrial carbon cycle to climate change. Remote sensing-derived spectral indices have been used to estimate photosynthetic phenology of terrestrial ecosystems, yet there are large uncertainties due to differences in leaf structure and canopy function between evergreen and deciduous trees. In this study, we used in-situ measured meteorology, the maximum rate of leaf-level CO 2 assimilation (A max), chlorophyll fluorescence and canopy color changes in evergreen and deciduous species to evaluate and compare the abilities of spectral indices for photosynthetic phenology modeling. Seasonal variation in A max is used as a proxy for photosynthetic phenology. Several indices were used, including the normalized difference vegetation index (NDVI), near-infrared reflectance vegetation index (NIRv), photochemical reflectance index (PRI), chlorophyll/carotenoid index (CCI), green-red vegetation index (GRVI), and green chromaticity coordinates (Gcc). We found that NIRv and PRI estimated phenological periods for Cedrus deodara and three deciduous trees all differed from A max by less than 5 days, and all were linearly related to A max (R2 > 0.6). CCI had less potential for A max modeling, while NDVI had the largest error in predicting A max. Gcc was a more accurate proxy for photosynthetic phenology than GRVI at the canopy scale. In addition, we found that the variability of different spectral indices in tracking photosynthetic phenology of evergreen and deciduous species was related to non-photochemical quenching processes. Especially for the fraction of absorbed light quenched by dynamic NPQ (ɸ NPQ) and the fraction of absorbed light quenched by sustained NPQ (ɸ f,D), they contribute more than 40 % to the variations of the NIRv and PRI spectral signals. Therefore, NIRv and PRI provide powerful tools for monitoring photosynthetic phenology, and future exploration of NIR v and PRI at larger spatial scales will favor the global plant phenology and carbon uptake modeling. [ABSTRACT FROM AUTHOR]

• The new tri-PRI tracks leaf-level xanthophyll epoxidation state dynamics in a mature eucalypt forest. • Indices using two-bands do not perform well. • The new formulation is robust to constitutive pigment pool size effects across the canopy profile. • tri-PRI achieved results comparable to PLSR and continuum removal using full spectrum data. Plants actively regulate excess absorbed energy to protect photosynthetic machinery through heat dissipation in a process known as non-photochemical quenching (NPQ), a process useful for quantifying plant health and productivity. NPQ can be indirectly measured in the visible wavelengths between 500 nm and 560 nm, most commonly through the Photochemical Reflectance Index (PRI). However, there remains a lack of consensus regarding the optimal functional form and band selection to calculate PRI for the purpose of measuring NPQ mechanisms. Here, we quantitatively evaluate the effectiveness of leaf-level parametric and non-parametric spectral formulations, band locations, and number of bands to track the xanthophyll pigment cycle in a tall mature Eucalypt forest. Subsequently, our recommended approach is the new 'tri-PRI' index robust to constitutive pigment pool sizes across the canopy profile. tri-PRI is a Triangular Vegetation Index (TVI) (tri-PRI = 0.5[(520 - 490)(R 545nm - R 490nm) - (545 – 490)(R 520nm - R 490nm)]) using three reflectance bands around 490 nm, 520 nm and 545 nm, and has a physiological photosynthetic basis. We found that tri-PRI significantly outperformed PRI and other two band combinations for quantifying the xanthophyll EPoxidation State 'EPS' (tri-PRI R2 = 0.75 versus PRI R2 = 0.23), as well as the Φ NPQ and Φ PSII active chlorophyll fluorescence quenching yields. The new band placement enhanced the dynamic EPS absorption peak, while the third band provided an additional normalisation to minimise the confounding effects of pigments with overlapping spectral features. tri-PRI also performed comparably to parametric and non-parametric hyperspectral techniques and formulations using continuous spectral regions, highlighting the utility of targeted multispectral indices over hyperspectral approaches. This leaf-level study represents a foundational step toward indirectly measuring dynamic photosynthetic activity across the canopy profile in a tall mature Eucalypt forest to inform upscaling efforts from above-canopy remote sensing platforms. The application of tri-PRI and other top-performing multi-band TVI formulations for predicting EPS presented here should be explored across different canopy types, temporal-, and spatial scales. [ABSTRACT FROM AUTHOR]

Abstract Due to its close link to the photosynthetic process, sun-induced chlorophyll fluorescence (F) opens new possibilities to study dynamics of photosynthetic light reactions and to quantify CO 2 assimilation rates. Although recent studies show that F is linearly related to gross primary production (GPP) on coarse spatial and temporal scales, it is argued that this relationship may be mainly driven by seasonal changes in absorbed photochemical active radiation (APAR) and less by the plant light use efficiency (LUE). In this work a high-resolution spectrometer was used to continuously measure red and far-red fluorescence and different reflectance indices within a sugar beet field during the growing season in 2015. Diurnal and seasonal developments were compared to eddy covariance derived GPP. Additionally, part of the time series coincided with a heatwave. The induced drought stress allowed us to observe F and its relationship to GPP under changing environmental conditions during the seasonal cycle. Across the season a strong linear relationship between GPP and F 760 was found. This relationship however, was mainly driven by changes in APAR and was strongly reduced under drought conditions. We could show that far-red fluorescence yield can explain 59% of the diurnal and 79% of the seasonal variance in the light use efficiency. However, an even stronger relationship between FY 760 and the structural vegetation index MTVI2 was found, implying that FY 760 is affected by seasonal structural changes of the canopy. Nevertheless, the seasonally de-trended FY 760 and PRI show that they share strong interdependencies with seasonal and diurnal LUE, in particular under drought stress conditions. Highlights • An extensive dataset was measured during the 2015 heat wave. • Under stress condition the relationship between F and GPP degreases significantly. • A revised PRI is proposed as indicator for diurnal changes in NPQ. • Seasonally de-trended rFY 760 and rPRI showed strong diurnal link to LUE. [ABSTRACT FROM AUTHOR]

The estimation of maximum carboxylation rate ( V cmax )—a critical determinant of the terrestrial carbon simulation—over space remains a challenging task. Inverting the V cmax through the sunlit gross primary productivity (GPP) is a possible solution if the key parameter sunlit light use efficiency ( ɛ sun ) could be acquired through remote sensing approaches. Previous studies have shown that the reflectance centered at 531 nm ( R 531 ) is very sensitive to variations of ɛ sun and the photochemical reflectance index ( PRI , the normalized difference index using R 531 and R 570 ) can be used as an indicator of ɛ sun at the leaf level though little is known about the PRI — ɛ sun relationship at the canopy level due to the mixing of sunlit and shaded leaves. In this study, the photochemical reflectance ratio ( PRR , defined as the ratio between R 531 and R 570 ) is proposed to enable the sunlit-shaded separation of the canopy reflectance observations acquired from a tower based multi-angular platform. The canopy PRR can be expressed as the algebraic sum of sunlit PRR and shaded PRR weighted by the visible portions of the sunlit canopy and the shaded canopy respectively. The visible portions from different angles were simulated using the 4-Scale model and the sunlit (/shaded) PRR was acquired through solving a set of equations describing the canopy PRR obtained from different angles. The relationships between the sunlit PRR ( PRR sun ) and ɛ sun were studied for a white pine stand (TP39) and a sugar maple stand (HA). At both sites, significant correlations between PRR sun and ɛ sun were obtained ( R 2 = 0.57 (TP39), 0.585 (HA), p < 0.001), showing the ability of PRR sun to track the variation of ɛ sun . Nevertheless, differences existed in the expressions of the PRR sun — ɛ sun relationship between TP39 and HA, a general expression could not be found. Further studies have shown that introducing the normalized difference vegetation index ( NDVI ) to correct PRR sun ( NDVI × PRR sun ) largely removed such differences, suggesting the potential of the NDVI corrected PRR sun in estimating the ɛ sun for different biomes. [ABSTRACT FROM AUTHOR]

The definition of irrigation schedules depends on the understanding of the response of key plant traits to different water restriction characteristics with the aim to avoid physiological impairment. In this study, different timings (at tuber initiation and bulking) and intensities (four soil moisture levels) of water restriction were tested in the potato crop. The temporal patterns of mid-morning or maximum, light saturated stomatal conductance ( g s_max ), recovery of net photosynthesis ( A recovery ), stem water potential (Ψ stem ), carbon isotope discrimination in tubers (Δ tuber ), plant water concentration ( PWC ), photochemical reflectance index ( PRI ) and crop water stress index ( CWSI ) were analyzed. Early-severe water restriction caused a drastic yield reduction, with low recovery of physiological responses ( g s_max , Δ tuber , Ψ stem , CWSI , A recovery ) after 15 days of post-restriction irrigation and even a continued reduction of some of them ( PWC , PRI ). It also caused a prolonged g s_max reduction below 0.05 mol H 2 O m −2 s −1 (≈ 5 μmol CO 2 m −2 s −1 of net photosynthesis) suggesting that this value defines a physiological severity threshold in potato, under which a metabolic impairment occurs. CWSI and PRI showed a close linear (R 2 = 0.76) and no linear (natural logarithm function, R 2 = 0.67) relationship with g s_max respectively. In cloudless dry environments, irrigation schedules in potato should aim to avoiding CWSI values higher than 0.4, especially until before of maximum canopy cover establishment. A close relationship between A recovery at maximum stress moment and yield reduction was found. The strong relationship between the measured traits (except PWC and Ψ stem ) and final yield at maximum stress moment found in the present study warrants further research on drought phenotyping immediately before post-restriction irrigation or when the defined severity threshold in potato is reached. [ABSTRACT FROM AUTHOR]

Photochemical reflectance index (PRI) is one of the best proxies to estimate the light use efficiency and photosynthetic activity of vegetation from remote sensing observations, especially if diurnal variations can be monitored. The calculation of PRI from leaf-level spectral reflectance measurements is unambiguous. Interpretation of the value of this index is more complicated, as it is affected by leaf structure and its carotenoid and chlorophyll content. Generally, a change in leaf-level PRI indicates a change in its photosynthetic capacity. At the scales of the canopy and beyond, various non-physiological factors modulate the leaf-level PRI signal inducing large angular and spatial variations in PRI. Specifically, previous studies have shown that within-canopy illumination variations and shadowing effects directly affect the PRI of a canopy. When observing a forest with a resolution finer than the size of a tree crown, large areas of shaded and sunlit foliage become visible. The spectral distribution of irradiance in these canopy regions is different from the average top-of-canopy irradiance used in the calculation of the canopy PRI. Thus, the leaf and canopy PRI can become decoupled. To date, no thorough analytical and empirical analysis of how the spectrally variable within-canopy light conditions cause apparent, non-physiological variation in canopy PRI has been published. In this study, we propose a new method to assess these PRI variations in structured vegetation from high spatial resolution (pixel size smaller than 1 m) imaging spectroscopy data. We used airborne imaging spectroscopy of boreal forest stands to evaluate the spectral irradiance in different locations inside the canopy and calculated a correction term for the canopy PRI estimates defined using top-of-canopy irradiance. We determined the maximum value of the correction term by sampling the most sunlit and shaded road surface locations adjacent to tree crowns. Results indicated that under the particular illumination-view geometry, irradiance variations decreased the canopy PRI by as much as 0.06 (relative change > 100%). The correction depended only slightly on atmospheric correction parameters. Finally, we reduced the illumination-related apparent variation in canopy PRI using the two-leaf canopy photosynthesis modeling scheme, canopy shadow fraction and the maximum correction term. In a test scene, the average illumination-corrected PRI was 0.027 smaller than non-corrected canopy PRI and showed no correlation with the shadow fraction, indicating a lack of down-regulation at the time of measurement. In theory, approach can be applied to all canopy level PRI measurements from towers, aircrafts and satellites under any observation geometry. However, further validation, preferably using in situ leaf reflectance data from different biomes, would be required before the algorithm can be routinely applied. [ABSTRACT FROM AUTHOR]

The relationship between the Photochemical Reflectance Index (PRI), Normalized Difference Vegetation Index (NDVI) and chlorophyll fluorescence along senescence was investigated in this work. Reflectance and radiance measurements were performed at canopy level in grass species presenting different photosynthetic metabolism: Avena sativa (C3) and Setaria italica (C4), at different stages of the natural senescence process. Sun induced-chlorophyll fluorescence at 760 nm (SIF 760 ) and the apparent fluorescence yield (SIF 760 / a, with a = irradiance at time of measurement) were extracted from the radiance spectra of canopies using the Fraunhofer Line Discrimination-method. The photosynthetic parameters derived from Kautsky kinetics and pigment content were also calculated at leaf level. Whilst stand level NDVI patterns were related to changes in the structure of canopies and not in pigment content, stand level PRI patterns suggested changes both in terms of canopy and of pigment content in leaves. Both SIF 760 / a and Φ PSII decreased progressively along senescence in both species. A strong increment in NPQ was evident in A. sativa while in S. italica NPQ values were lower. Our most important finding was that two chlorophyll fluorescence signals, Φ PSII and SIF 760 /a, correlated with the canopy PRI values in the two grasses assessed, even when tissues at different ontogenic stages were present. Even though significant changes occurred in the Total Chlr/Car ratio along senescence in both studied species, significant correlations between PRI and chlorophyll fluorescence signals might indicate the usefulness of this reflectance index as a proxy of photosynthetic RUE, at least under the conditions of this study. The relationships between stand level PRI and the fluorescence estimators (Φ PSII and SIF 760 /a) were positive in both cases. Therefore, an increase in PRI values as in the fluorescence parameters would indicate higher RUE. [ABSTRACT FROM AUTHOR]

This study systematically analyzed the performance of multivariate hyperspectral vegetation indices of rice ( Oryza sativa L. ) in estimating the arsenic content in agricultural soils. Field canopy reflectance spectra was obtained in the jointing-booting growth stage of rice. Newly developed and published multivariate vegetation indices were initially calculated to estimate soil arsenic content. The well-performing vegetation indices were then selected using successive projections algorithm (SPA), and the SPA selected vegetation indices were adopted to calibrate a multiple linear regression model for estimating soil arsenic content. Results showed that a three-band vegetation index ( R 716 − R 568 )/( R 552 − R 568 ) performed best in the newly developed vegetation indices in estimating soil arsenic content. The photochemical reflectance index (PRI) and red edge position (REP) performed well in the published vegetation indices. Moreover, the linear combination of two vegetation indices (( R 716 − R 568 )/( R 552 − R 568 ) and REP) selected using SPA improved the estimation of soil arsenic content. These results indicated that the newly developed three-band vegetation index ( R 716 − R 568 )/( R 552 − R 568 ) might be recommended as an indicator for estimating soil arsenic content in the study area. PRI and REP could be used as universal vegetation indices for monitoring soil arsenic contamination. [ABSTRACT FROM AUTHOR]

Observations of terrestrial chlorophyll fluorescence and the Photochemical Reflectance Index ( PRI ) from space have the potential to improve estimates of global carbon exchange. However the relationship between photosynthetic rate and these measurements is complicated by several factors that relate to the dissipation of absorbed light energy via both photochemical (photosynthesis) and non-photochemical pathways. Numerical simulations of physiological remote sensing signals require the coupling of physically-based radiative transfer models with models of physiological dynamics. These schemes provide the quantitative frameworks from which physiological information can be extracted from remote sensing observations of vegetation, helping to resolve the aforementioned complexities. We present such a framework that links physiological fluorescence theory with spectral remote sensing type measurements at the leaf scale. We show how a simple expression can be used to predict the quantum yield of photochemistry (Φ PSII ), a proxy for photosynthetic efficiency, from spectral measurements and modelled non-photochemical quenching ( NPQ ). We tested two alternate models of NPQ ; one process-based ( PHOTOII ) and the other empirical, based on visible region reflectance changes (the PRI ). We used a Monte Carlo Radiative Transfer ( MCRT ) model to retrieve the separated yields of chlorophyll fluorescence from photosystems II and I. Measurements of dynamic spectral fluorescence, the PRI , hemispherical reflectance and transmittance, saturation pulse integrated fluorescence and pigment contents were collected from maple leaves and used to calibrate and validate the modelling framework. Both NPQ models reproduced the observed photochemical and non-photochemical dynamics. Future work is recommended to scale the framework across space, time and species. [ABSTRACT FROM AUTHOR]

• MODIS ocean band derived PRI showed better potential in modeling phenology. • Both flux and ground data supported the use of PRI for phenology predicting. • Structural VIs may underestimate greenness of the Northern Hemisphere. Vegetation phenology is a sensitive indicator of ecosystem responses to climate change, and thus the accurate estimation of vegetation phenology is critical to evaluate the impact of climate change on terrestrial ecosystems. Common structural vegetation indices (VIs) such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Near-infrared Reflectance of Vegetation (NIRv) and Plant Phenology Index (PPI), are the most widely used indicators of phenology, but they have limited potential in tracking autumn phenology, especially for evergreen species with low seasonal variability of canopy greenness. Given the important role of carotenoid pigments in regulating photosynthetic activity and plant phenology, we hypothesize that satellite-based indicators of leaf pigments derived from MODIS ocean bands could be useful for phenology modeling. Using 624 site-years of flux data at 84 FLUXNET sites and 9979 ground observations at 138 PEP725 sites, we first explored the potential of different forms of scaled photochemical reflectance index (sPRI ref) in monitoring photosynthetic activity, and found that band 10 and band 13 were more suitable for tracking gross primary productivity (GPP) than other reference bands. By comparing with canopy photosynthetic phenology, sPRI 10 and sPRI 13 showed improved representation of phenological transitions (the start and end of growing season, SOS and EOS, respectively) than structural VIs. In spring, all VIs exhibited comparable performances for estimating SOS at deciduous broadleaf forests (DBF) and grasslands (GRA) sites; however, sPRI 10 and sPRI 13 were better predictors of SOS than structural VIs at evergreen needleleaf forests (ENF) and mixed forests (MF) sites. In autumn, sPRI 10 and sPRI 13 showed improved predictive strength of EOS than structural VIs for ENF, MF and GRA sites. Further investigations using the ground observed phenological records also confirmed the improved performances of sPRI 10 and sPRI 13 for both SOS and EOS estimation. We also investigated the spatial patterns of sPRI 10 -derived SOS and EOS over the Northern Hemisphere with respect to different plant functional types. We showed that sPRI 10 reliably tracked plant phenology with 83.0% and 78.8% success in detecting SOS and EOS, respectively. Spatial patterns of SOS exhibited obvious latitudinal gradients, while EOS showed a strong regional heterogeneity. In addition, sPRI 10 predicted an overall earlier SOS (61.8%) and later EOS (51.2%) than the MODIS phenology product (VNP22Q2 v001) estimated from structural VI, suggesting the latter underestimated the greening potential of the Northern Hemisphere. Our results suggest that MODIS PRI could be useful to monitor vegetation phenology, and further reveal the importance of underappreciated carotenoid pigments in tracking plant seasonal changes, particularly in autumn months. [ABSTRACT FROM AUTHOR]

• Fluorescence and photosynthesis were not linearly related across a phosphorus gradient. • Quantum use efficiency (Φ PSII) could not be predicted from fluorescence yield alone. • Pigment corrected PRI and fluorescence ratio allowed to estimate Φ PSII at leaf level. Sun-induced chlorophyll fluorescence (SIF) is one of the most promising remote-sensing signals to assess spatio-temporal variation in photosynthesis. Yet, it has been shown that the positive linear relationship of SIF and photosynthesis, often reported from satellite and proximal remote sensing, is mainly driven by the amount of absorbed photosynthetic active radiation (APAR). By normalizing SIF by APAR these structural first-order effects can accounted for and SIF is then reflecting physiological regulation of photosynthetic efficiency. However, because of the confounding contribution of non-photochemical energy dissipation, the relationship between SIF and photosynthetic efficiency is non-linear, and therefore additional measurements have to be included to constrain the predictions of photosynthetic efficiency and photosynthetic electron transport. We grew Zea mays at different phosphorus (P) levels to assess if P-induced reduction in quantum efficiency of PSII (Φ PSII), can be estimated by the fluorescence efficiency parameters, APAR normalized fluorescence (F yield) and the ratio of the two emitted fluorescence peaks (F ↑ratio), at leaf level. Results were compared to the photochemical reflectance index (PRI), a well-established index related to the activity of the xanthophyll cycle, a protection mechanism which activates under light-stress conditions. We demonstrate that the relationship between Φ PSII and F yield is non-monotonic across a P limitation gradient, rendering the prediction of Φ PSII by F yield alone unfeasible. We show, however, that the pigment corrected PRI (cPRI) and F ↑ratio (cF ↑ratio) share a strong linear relationship with Φ PSII , thereby enabling the estimation of Φ PSII. We demonstrate that a compensation for reabsorption effects improved the estimation of Φ PSII by F ratio at foliar level. This may allow improved predictions of photosynthetic light use efficiency parameters without the need of measuring green APAR. [ABSTRACT FROM AUTHOR]

• The PRI as an indicator of NPQ to characterize the change in heat dissipation. • SIF is strongly affected by radiation, while PRI is sensitive to soil moisture. • PRI can be used to improve the relationship between GPP and SIF. The sun-induced chlorophyll fluorescence (SIF) is directly related to the photosynthesis of winter wheat and has a good linear relationship with the gross primary production (GPP). However, the relationship of SIF and GPP is still uncertain under different soil water content conditions. The sun-induced chlorophyll fluorescence, GPP and non-photochemical quenching (NPQ) are the three ways of photosynthetically active radiation in plants. The photochemical reflectance index (PRI) can be used as a proxy indicator of NPQ to characterize the change in heat dissipation during photosynthesis process of winter wheat. To detect the impact of soil water content on winter wheat photosynthesis and SIF and GPP relationship, based on the ground measurement data at Zhaoxian Experimental Station in northern China during the growing season in 2018 and the simulated data by the SCOPE model, we use PRI to improve the GPP model estimated by SIF. The results indicate that: (1) PRI is sensitive to soil water content (R2 = 0.64), so it can be used to improve the estimation of GPP based on SIF under different soil water conditions; (2) For the ground measurement data, PRI obv can improve the estimation accuracy of GPP obv by SIF obv. Under different soil water content (SWC) conditions, the relationship between GPP obv and SIF obv is significantly correlated (R2 = 0.33–0.45, p < 0.01), and PRI obv can be used to improve the estimation between GPP obv and SIF obv (R2 = 0.57–0.62, p < 0.01); (3) The simulation results of the SCOPE model show that the simulation effect of the model can be better optimized by adding PRI under the condition of relatively dry soil (△R2 = 0.13–0.17). Our research suggests that PRI can be added when estimating GPP using SIF information, especially when winter wheat is under low soil water content conditions. [ABSTRACT FROM AUTHOR]

Vegetation responds at varying temporal scales to changing soil water availability. These process dynamics complicate assessments of plant-water relations but also offer various access points to advance understanding of vegetation responses to environmental change. Remote sensing (RS) provides large capacity to quantify sensitive and robust information of vegetation responses and underlying abiotic change driver across observational scales. Retrieved RS based vegetation parameters are often sensitive to various environmental and plant specific factors in addition to the targeted plant response. Further, individual plant responses to water limitation act at different temporal and spatial scales, while RS sampling schemes are often not optimized to assess these dynamics. The combination of these aspects complicates the interpretation of RS parameter when assessing plant-water relations. We consequently aim to advance insight on the sensitivity of physiological, biochemical and structural RS parameter for plant adaptation in response to emerging soil water limitation. We made a field experiment in maize in Tuscany (Central Italy), while irrigation was stopped in some areas of the drip-irrigated field. Within a period of two weeks, we measured the hydraulic and physiological state of maize plants in situ and complemented these detailed measurements with extensive airborne observations (e.g. sun-induced chlorophyll fluorescence (SIF), vegetation indices sensitive for photosynthesis, pigment and water content, land surface temperature). We observe a double response of far-red SIF with a short-term increase after manifestation of soil water limitation and a decrease afterwards. We identify different response times of RS parameter representing different plant adaptation mechanisms ranging from short term responses (e.g. stomatal conductance, photosynthesis) to medium term changes (e.g. pigment decomposition, changing leaf water content). Our study demonstrates complementarity of common and new RS parameter to mechanistically assess the complex cascade of functional, biochemical and structural plant responses to evolving soil water limitation. • SIF shows a temporally graduated dual response to decreasing soil water. • SIF responds faster than other RS proxies to decreasing soil water. • Rigorous normalization is essential to derive subtle plant responses from RS data. [ABSTRACT FROM AUTHOR]

Abstract: Rapid and non-destructive diagnosis of plant N status is highly required in order to optimise N fertilizer management and use-efficiency. Additionally to handheld devices for measurements of chlorophyll indices (e.g., SPAD meter) parameters of canopy reflectance via remote sensing approaches are intensively investigated and the photochemical reflectance index (PRI) appears to be a reliable indicator for changes of the epoxidation state of xanthophyll cycle pigments. In order to assess the suitability of a handheld PRI as an additional tool for N diagnosis, rice plants were grown in a nutrient solution experiment with seven N-supply levels (0.18–5.71mM) and CI (SPAD) and PRI values and chlorophyll fluorescence parameters measured 20 and 28days after onset of treatments. N-supply had effects on both CI (SPAD) and PRI values with a more reliable differentiation between levels. Maximum quantum yield of PSII (Fv /Fm ), actual efficiency of PSII photochemistry (ФPSII ) and regulated non-photochemical quenching (ФNPQ ) did not differ significantly between N levels. Non-photochemical quenching (NPQ) and fast- relaxing NPQ (NPQF ) were significantly affected by N-supply. NPQ and NPQF , but not the slow-relaxing component (NPQS ), were correlated with CI (SPAD) and PRI values. This finding which has not been reported for N-supply effects so far is indirect evidence that low N-supply induced xanthophyll cycle activity and that PRI values are able to indicate this at least in plants subject to severe N deficiency. [Copyright &y& Elsevier]

Abstract: Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reflectance Index (PRI) derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efficiency. We examined and synthesized the scientific literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efficiency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efficiency (RUE; the ratio between carbon uptake and light absorbed by vegetation) variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE–PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efficiencies. PRI accounted for 42%, 59% and 62% of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation (FPAR), estimated with NDVI-like indices, PRI enables improved assessment of carbon fluxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors. [Copyright &y& Elsevier]

Abstract: Two radiative transfer canopy models, SAIL and the two-layer Markov-Chain Canopy Reflectance Model (MCRM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the photochemical reflectance index in a cornfield. In situ hyperspectral measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles (ψ) at three different view zenith angles (θ v), and later used to validate model outputs. Field observations of PRI for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, as a function of both θ v and ψ. Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, the MCRM-simulated PRI values showed satisfactory correlation and RMSE, as compared to in situ values. However, the performance of the MCRM model was significantly improved after defining a lower canopy layer comprised of shaded leaves beneath the upper sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; but unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. LAI showed the most significant impact on MCRM-simulated PRI among the parameters studied. This research shows the importance of hyperspectral and narrow band sensor studies, and especially the necessity of including the green wavelengths (e.g., 531nm) on satellites proposing to monitor carbon dynamics of terrestrial ecosystems. [Copyright &y& Elsevier]

Abstract: Recent advances in understanding relationships between spectral reflectance of vegetation canopies and the structural and physiological drivers of canopy-atmosphere carbon dioxide exchange highlight the potential for using narrowband spectral vegetation indices to spatially scale CO2 fluxes beyond the area of a tower footprint. However, ground reference observations of narrowband spectral reflectance in support of satellite observations can be challenging to obtain because (1) automated sampling of both upwelling and downwelling radiation is required over extended time periods to characterize diurnal and seasonal variability, (2) hyperspectral spectroradiometer data and hardware can be sensitive to environmental factors such as temperature and moisture, and (3) hyperspectral spectroradiometers are expensive, greatly limiting prospects for widespread automated sampling. We have therefore developed the QuadPod: a simple, lightweight, relatively low cost and low power sensor capable of continuously measuring upwelling and downwelling radiation in 10nm wavebands centered at 532nm, 568nm, 676nm, and 800nm. QuadPod measurements can be combined to calculate spectral reflectance indices (e.g., the photochemical reflectance index, PRI; and the normalized difference vegetation index, NDVI) useful for modeling canopy-atmosphere carbon exchange. The basic QuadPod instrument design described here can be implemented using any combination of optical filters in order to calculate other spectral vegetation indices. [Copyright &y& Elsevier]

Abstract: Estimation of photosynthetic light use efficiency (ε) from satellite observations is an important component of climate change research. The photochemical reflectance index, a narrow waveband index based on the reflectance at 531 and 570 nm, allows sampling of the photosynthetic activity of leaves; upscaling of these measurements to landscape and global scales, however, remains challenging. Only a few studies have used spaceborne observations of PRI so far, and research has largely focused on the MODIS sensor. Its daily global coverage and the capacity to detect a narrow reflectance band at 531 nm make it the best available choice for sensing ε from space. Previous results however, have identified a number of key issues with MODIS-based observations of PRI. First, the differences between the footprint of eddy covariance (EC) measurements and the MODIS footprint, which is determined by the sensor''s observation geometry make a direct comparison between both data sources challenging and second, the PRI reflectance bands are affected by atmospheric scattering effects confounding the existing physiological signal. In this study we introduce a new approach for upscaling EC based ε measurements to MODIS. First, EC-measured ε values were “translated” into a tower-level optical PRI signal using AMSPEC, an automated multi-angular, tower-based spectroradiometer instrument. AMSPEC enabled us to adjust tower-measured PRI values to the individual viewing geometry of each MODIS overpass. Second, MODIS data were atmospherically corrected using a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which uses a time series approach and an image-based rather than pixel-based processing for simultaneous retrievals of atmospheric aerosol and surface bidirectional reflectance (BRDF). Using this approach, we found a strong relationship between tower-based and spaceborne reflectance measurements (r 2 =0.74, p <0.01) throughout the vegetation period of 2006. Swath (non-gridded) observations yielded stronger correlations than gridded data (r 2 =0.58, p <0.01) both of which included forward and backscatter observations. Spaceborne PRI values were strongly related to canopy shadow fractions and varied with different levels of ε. We conclude that MAIAC-corrected MODIS observations were able to track the site-level physiological changes from space throughout the observation period. [Copyright &y& Elsevier]

Gross primary productivity (GPP) changes occur at different time-scales and due to various mechanisms such as variations in leaf area, chlorophyll content, rubisco activity, and stomatal conductance. Diagnostic estimates of primary productivity are obviously error prone when these changes are not accounted for. Additional complications arise when factors inuencing a biome-specific maximum light use efficiency (LUE) must be estimated over a large area. In these cases a direct estimation of ecosystem LUE could reduce uncertainty of GPP estimates. Here, we analyse whether a MODIS-based photochemical reectance index (PRI) is a useful proxy for the light use efficiency of a Mediterranean Quercus ilex forest. As the originally proposed reference band for PRI is not available on MODIS, we tested the reference bands 1 (620–670 nm), 4 (545–565 nm), 12 (546–556 nm), 13 (662–672 nm), and 14 (673–683 nm) using different atmospheric correction algorithms. We repeated the analysis with different temporal resolutions of LUE (half-hourly to daily). The strongest correlation between LUE and PRI was found when considering only a narrow range of viewing angles at a time (especially 0–10° and 30–40°). We found that the MODIS-based PRI was able to track ecosystem LUE even during severe summer time water limitation. For this Mediterranean-type ecosystem we could show that a GPP estimation based on PRI is a huge improvement compared to the MODIS GPP algorithm. In this study, MODIS spectral band 1 turned out to be the most suitable reference band for PRI, followed by the narrow red bands 13 and 14. As to date no universally applicable reference band was identified in MODIS-based PRI studies, we advocate thorough testing for the optimal band combination in future studies. [Copyright &y& Elsevier]

This paper presents a methodology for water stress detection in crop canopies using a radiative transfer modelling approach and the Photochemical Reflectance Index (PRI). Airborne imagery was acquired with a 6-band multispectral camera yielding 15 cm spatial resolution and 10 nm FWHM over 3 crops comprising two tree-structured orchards and a corn field. The methodology is based on the PRI as a water stress indicator, and a radiative transfer modelling approach to simulate PRI baselines for non-stress conditions as a function of leaf structure, chlorophyll concentration (Cab), and canopy leaf area index (LAI). The simulation work demonstrates that canopy PRI is affected by structural parameters such as LAI, Cab, leaf structure, background effects, viewing angle and sun position. The modelling work accounts for such leaf biochemical and canopy structural inputs to simulate the PRI-based water stress thresholds for non-stress conditions. Water stress levels are quantified by comparing the image-derived PRI and the simulated non-stress PRI (sPRI) obtained through radiative transfer. PRI simulation was conducted using the coupled PROSPECT-SAILH models for the corn field, and the PROSPECT leaf model coupled with FLIGHT 3D radiative transfer model for the olive and peach orchards. Results obtained confirm that PRI is a pre-visual indicator of water stress, yielding good relationships for the three crops studied with canopy temperature, an indicator of stomatal conductance (r 2 =0.65 for olive, r 2 =0.8 for peach, and r 2 =0.72 for maize). PRI values of deficit irrigation treatments in olive and peach were consistently higher than the modelled PRI for the study sites, yielding relationships with water potential (r 2 =0.84) that enabled the identification of stressed crowns accounting for within-field LAI and Cab variability. The methodology presented here for water stress detection is based on the visible part of the spectrum, and therefore it has important implications for remote sensing applications in agriculture. This method may be a better alternative to using the thermal region, which has limitations to acquire operationally high spatial resolution thermal imagery. [Copyright &y& Elsevier]

Abstract: We show that observed co-variations at sub-hourly time scales between the photochemical reflectance index (PRI) and canopy light use efficiency (LUE) over a Douglas-fir forest result directly from sub-hourly leaf reflectance changes in a 531 nm spectral window roughly 50 nm wide. We conclude then, that over a forest stand we are observing the direct effects of photosynthetic down-regulation on leaf-level reflectance at 531 nm. Key to our conclusion is our ability to simultaneously measure the LUE and reflectance of the Douglas-fir stand as a function of shadow fraction from the “hot spot” to the "dark spot"dark spot” and a new finding herein, based on radiative transfer theory, that the magnitude of a normalized reflectance difference index (NDRI) such as PRI can vary with shadow fraction only in case the reflectance of the shaded and sunlit leaves differ in at least one of the NDRI bands. Our spectrometer measurements over a nearly 6 month period show that at a forest stand scale, only two NDRIs (both containing a band near 570 nm) vary with shadow fraction and are correlated with LUE; an NDRI with a band centered at 531 nm roughly 50 nm wide, and another near 705 nm. Therefore, we are able to conclude that only these two bands'' reflectance differ between the sunlit and the shaded elements of the canopy. Their reflectance changes on time scales of a few minutes or less. Our observations also show that the reflectance changes at 531 nm are more highly correlated with variations in canopy light use efficiency when only sunlit canopy elements are viewed (the hot spot), than when only shaded elements (the dark spot) are viewed. Taken together then, these results demonstrate that the observed sub-hourly changes in foliage reflectance at 531 nm and 705 nm can only result from corresponding variations in photosynthetic rates. The importance of our results are as follows: (1) We show that variations in PRI with LUE are a direct result of rapid changes in foliage reflectance at 531 nm resulting from photosynthetic down-regulation, and can be observed at forest scales. (2) Our findings also suggest a new sensor and methodology for the direct retrieval from space of changes in forest LUE by measuring PRI as a function of shadow fraction using a multi-angle spectrometer simultaneously retrieving both shadow fraction and PRI. [Copyright &y& Elsevier]

Abstract: Direct estimation of photosynthetic light-use efficiency (LUE) from space would be of significant benefit to LUE-based models which use inputs from remote sensing to estimate terrestrial productivity. The Photochemical Reflectance Index (PRI) has shown promise in tracking LUE at the leaf- to small canopy levels, but its use at regional to global scales still remains a challenge. In this study, we used different formulations of PRI calculated from the MODIS ocean band centered at 531 nm and a set of alternative reference bands at 488, 551, and 678 nm to explore the relationship between PRI and LUE where LUE was measured at eight eddy covariance flux towers located in the boreal forest of Saskatchewan, Canada. The magnitude and variability of LUE was significantly lower at the times when useful MODIS ocean band images were available (i.e. around midday under clear-sky conditions) relative to the rest of the growing season. PRI678 (reference band at 678 nm) showed the strongest relationship (r 2 =0.70) with LUE90a (i.e. 90-minute mean LUE calculated using Absorbed Photosynthetically Active Radiation, APAR), but only when all sites were combined. Overall, the relationships between the MODIS PRIs and LUE90a were always stronger for observations closer to the backscatter direction and there were no significant differences in the strength of the correlations whether LUE was calculated based on incident PAR or on APAR. Predictions of ecosystem photosynthesis at the time of the MODIS overpasses were significantly improved by multiplying either PAR or APAR by MODIS PRI (r 2 improved from 0.09 to 0.44 and 0.54 depending on the PRI formulation). We used our PRI-LUE model to create a regional LUE90a map for the three cover types covering 47,500 km2 around the flux sites. The MODIS PRI-derived LUE90a map appeared to capture more realistic spatial heterogeneity of LUE across the landscape compared to a daily LUE map derived using the look-up table in the MODIS GPP (MOD17) algorithm. While our LUE map is only a snapshot of minimum regional LUE90a values, with appropriate gap-filling methods it could be used to improve regional-scale monitoring of GPP. Moreover, the strong relationship between midday and daily LUE on clear days (r 2 =0.93) indicates that instantaneous MODIS observations of LUE90a could be used to estimate daily LUE. Finally, pixel shadow fraction from the 5-Scale geometric-optical model was closely related to both MODIS PRI and tower-derived LUE suggesting that differences in stand leaf area and in diffuse illumination among flux sites play a role in the relationship we observed between LUE and MODIS PRI. [Copyright &y& Elsevier]

Abstract: View angle effects present in spectral vegetation indices can either be regarded as an added source of uncertainty for variable retrieval or as a source of additional information, enhancing the variable retrieval; however, the magnitude of these angular effects remains for most indices unknown or unquantified. We use the ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy) providing spaceborne imaging spectrometer and multiangular data to assess the reflectance anisotropy of broadband as well as recently developed narrowband indices. Multiangular variability of Hemispherical Directional Reflectance Factor (HDRF) is a prime factor determining the indices´ angular response. Two contrasting structural vegetation types, pine forest and meadow, were selected to study the effect of reflectance anisotropy on the angular response. Calculated indices were standardized and statistically evaluated for their varying HDRF. Additionally we employ a coupled radiative transfer model (PROSPECT/FLIGHT) to quantify and substantiate the findings beyond an incidental case study. Nearly all tested indices manifested a prominent anisotropic behaviour. Apart from the conventional broadband greenness indices [e.g. Simple Ratio Index (SRI), Normalized Difference Vegetation Index (NDVI)], light use efficiency and leaf pigment indices [e.g. Structure Insensitive Pigment Index (SIPI), Photochemical Reflectance Index (PRI) and Anthocyanin Reflectance Index (ARI)] did express significant different angular responses depending on the vegetation type. Following the quantification of the impact, we conclude that the angular-dependent fraction of non-photosynthetic material is of critical importance shaping the angular signature of these VIs. This work highlights the influence of viewing geometry and surface reflectance anisotropy, particularly when using light use efficiency and leaf pigment indices. [Copyright &y& Elsevier]

Abstract: The relationships between ecosystem-level light use efficiency (LUE) obtained from an eddy covariance flux tower and MODIS-derived values of a scaled Photochemical Reflectance Index (sPRI) were investigated for a boreal aspen stand (Populus tremuloides Michx.) in Saskatchewan, Canada. Using MODIS ocean band 11 at 531 nm, we tried to detect variations in canopy reflectance related to the xanthophyll cycle. We tested several other MODIS bands as the reference band because the 570 nm reference band that had been determined to be optimum for calculating PRI in earlier studies is not available on MODIS. While LUE varied greatly within the 2001, 2002, and 2003 growing seasons, the Normalized Difference Vegetation Index (NDVI) calculated from tower sensors remained stable. LUE had a negative exponential relationship with vapor pressure deficit and air temperature, and was at a maximum when absorbed PAR was <200 μmol m−2 s−1. The range and magnitude of tower-based LUE values were smaller on clear days, when MODIS acquisitions were possible, than they were overall. Furthermore, the orbital parameters of the Terra and Aqua satellites restricted MODIS acquisitions to a 2.5-h period in early afternoon at our study site when LUE values were typically lower than they were earlier in the day. Strong correlations between MODIS-sPRI and LUE were found only for backscatter reflectance scenes when band 13 (667 nm) was used as the reference band. The correlations were higher for sPRI calculated from top of atmosphere reflectances than for surface reflectances (r 2 =0.76 and 0.53, respectively). The absolute backscatter reflectance of bands 11, 12 (551 nm), and 13 all decreased with increasing LUE. The decrease in band 13 suggests that the correlation between sPRI and LUE that we observed was caused by reductions in canopy chlorophyll content from 2001 to 2003 and/or by increased visibility of brighter non-photosynthetic material. Regional values of sPRI from 260 deciduous forest pixels in the 10,000 km2 vicinity of the tower for two contrasting days, one in 2001 and one in 2003, were consistent with that observed for the flux tower footprint. [Copyright &y& Elsevier]

The emerging consistency of the relationship between biochemical, optical, and odorous signals emitted by plants and ecosystems offers promising prospects for continuous local and global monitoring of the energetic status of plants and ecosystems, and therefore of their processing of energy and matter. [ABSTRACT FROM AUTHOR]

In the coming years, Earth Observation missions like the FLuorescence EXplorer (FLEX) will acquire the radiance signal from the visible to the near-infrared at a very high spectral resolution, enabling exciting prospects for new insights in satellite-based photosynthetic studies. In this context, the process of de-coupling atmospheric and vegetation-related spectral signatures will become essential to guarantee a reliable estimation of the vegetation photosynthetic activity from space. Dynamic changes related to the vegetation photosynthetic status result in subtle contributions to the top of atmosphere radiance signal, e.g. due to the emission of the solar-induced chlorophyll fluorescence (~ 650–800 nm) or due to changes in surface reflectance spectra (500–600 nm) indicating variations in the vegetation photoprotection and light use efficiency. Conversely, atmospheric effects (molecular and aerosol absorption and scattering) dominate the spectral interval of interest for vegetation studies. This article presents a comprehensive overview of the atmospheric radiative effects caused by aerosols, ozone (O 3), water vapor (H 2 O), oxygen (O 2), and atmospheric pressure and temperature changes within the visible and near-infrared spectral interval, and paying special attention to the co-occurring vegetation-related spectral changes associated with the fluorescence emission and the activation of the photoprotection mechanisms. Since the largest uncertainties in the atmospheric correction process are associated with the characterization of the aerosol radiative effects, this work largely concentrates on the satellite retrieval-related implications under different aerosol absorbing and scattering scenarios on a global scale. Through a simulation exercise, it is evaluated to what extent aerosol climatology could influence the accuracy of satellite-derived surface apparent reflectance spectra impacting; therefore, any vegetation-related satellite product on a seasonal and global scale. • Impact of aerosol characterization inaccuracies on the PRI region • Assessment of atmospheric effects on the fluorescence emission range • Aerosol error propagation assessment on vegetation dynamics using climatology data • O2-A and -B features: evaluation of aerosol, temperature and pressure conditions [ABSTRACT FROM AUTHOR]

In open forest canopies, such as in boreal forests, forest floor can contribute significantly to the observed top of canopy reflectance. In order to retrieve the biophysical properties of the tree layer, correcting for forest floor is essential. Traditionally, the algorithms for retrieval of forest floor reflectance depend on tree layer information such as leaf area index, canopy cover, and site fertility. To overcome these circular dependencies, we propose an algorithm that can be applied only using airborne remote sensing data. We acquired airborne hyperspectral imagery over the Hyytiälä forest research station (61°50′N, 24°17′E) in central Finland on July 3rd in 2015 using a hyperspectral pushbroom line scanner. The image data had a spectral resolution of 4.6 nm, and the spatial resolution was 0.6 m. We developed a linear spectral unmixing algorithm, which is based on the definition of the reflectance factor, taking into account the variation of incident irradiance inside the canopy. The weights of the mixture can be computed from tree canopy gap fractions, a tree species insensitive leaf albedo, and average tree stand reflectance. Canopy gap fractions were retrieved with empirical methods available in scientific literature. The forest floor reflectance in the near-infrared increased with site fertility in agreement with the forest floor field measurements. Moreover, we found that in near infrared, the reflectance of moderately rich and moist upland forests was significantly different from all other fertility classes. Finally, we tested the reflectance decomposition on the photochemical reflectance index (PRI) known to be heavily affected by understory reflectance and canopy structure, and the forest PRI to be decoupled from the PRI of the over- and understory. • Airborne hyperspectral imagery used to estimate boreal forest floor reflectance. • Separation of forest floor and overstory reflectance without field stand variables. • Boreal forest floor reflectance in near-infrared increases with site fertility. • Calculated forest floor reflectance matches moist upland spectra. • Forest floor reflectance in NIR significantly different among fertility classes. [ABSTRACT FROM AUTHOR]

We studied the influence of changing carotenoid pigments on the sensitivity of the photochemical reflectance index (PRI) to photosynthesis dynamics. The goal of the measurements was to examine how the introduction of ΔPRI into the working dataset can improve the estimation of photosynthesis. Spectral and photosynthetic characteristics of European beech and Norway spruce saplings were periodically measured in growth chambers with an adjustable irradiance and temperature. Patterns of environmental changes inside the growth chambers were created by periodic changes in irradiance and temperature. Four general irradiance periods lasting 10–12 days each were established. Introduced irradiance regimes varied in the sum of daily irradiance and amplitude of irradiance changes. Temperature was changed with more complex patterns to induce changes in xanthophyll cycle pigments at various time scales within these regimes. Our measurements confirmed the PRI linkage to photosynthetic light use efficiency (LUE). However, the strength of this connection was found to be dependent on changing pigment concentrations, specifically on the change in the ratio of chlorophylls to carotenoids. Furthermore, a negative interference in photosynthesis estimation from PRI was recorded if the temperature was lowered overnight to 12 °C. The differential PRI (ΔPRI), calculated as the simple difference between the PRI value measured during the daytime period and in early morning (PRI 0), revealed a decreased effect from pigments and cold temperature on LUE estimation. The regression analysis among all measured data identified an increased association between PRI and LUE following the introduction of ΔPRI from R 2 = 0.26 to 0.69 in beech and from R 2 = 0.61 to 0.77 in spruce data. The analyses showed that both leaf carotenoid concentrations and the conversion state of xanthophyll cycle pigments played a significant role in determining PRI and PRI 0 values and that the accurate assessment of these pigments in PRI across multiple levels of stress from irradiance and temperature might improve estimations of LUE through ΔPRI. In our data, ΔPRI appeared to be a good measure of photosynthesis, the dynamics of which differed between beech and spruce saplings upon switching temperatures. • We studied PRI dynamics in changing irradiance and temperature setup. • Sensitivity of PRI to LUE was dependent on the changing ratio of Chl a+b /Car x+c. • Interference from Chl a+b /Car x+c in LUE estimation was lowered when using ΔPRI. • Effect of low temperature on LUE estimation from PRI was reduced with ΔPRI. • Leaf area index of trees appeared to be an important driver in observed relationships. [ABSTRACT FROM AUTHOR]