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The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four growing seasons. The Photochemical Reflectance Index (PRI) and solar induced chlorophyll fluorescence (SIF), were derived. SIF retrievals were accomplished in the two telluric atmospheric oxygen absorption features centered at 688 nm (O2-B) and 760 nm (O2-A). The PRI and SIF were examined in conjunction with GPP and LUE determined by flux tower-based measurements. All of these fluxes, environmental variables, and the PRI and SIF exhibited diurnal as well as day-to-day dynamics across the four growing seasons. Consistent with previous studies, the PRI was shown to be related to LUE (r2 = 0.54 with a logarithm fit), but the relationship varied each year. By combining the PRI and SIF in a linear regression model, stronger performances for GPP estimation were obtained. The strongest relationship (r2 = 0.80, RMSE = 0.186 mg CO2/m2/s) was achieved when using the PRI and SIF retrievals at 688 nm. Cross-validation approaches were utilized to demonstrate the robustness and consistency of the performance. This study highlights a GPP retrieval method based entirely on hyperspectral remote sensing observations. [ABSTRACT FROM AUTHOR]

In the last three decades, substantial advancements have been made in understanding the global carbon cycle. Some of these advancements involve using the fraction of absorbed photosynthetically active radiation (fAPAR) by an entire canopy (fAPARcanopy) and/or the Normalized Difference Vegetation Index (NDVI) in modeling studies. In spite of these advancements, large uncertainties still remain. Zhang (Remote Sens. Environ., 2005) [1] tried to mitigate some of these uncertainties with the concept of using fAPAR that is restricted to the foliage chlorophyll (fAPARchl) instead of the entire canopy. In this current study, we calculated fAPARcanopy, fAPARchl, and foliage non-chlorophyll fAPAR (fAPARnon\mathchar "702D chl) for the Harvard Forest using a radiative transfer model and multi-temporal Earth Observing One (EO-1) Hyperion satellite images. The canopy-level proportions of foliar chlorophyll and non-chlorophyll absorption were determined at different seasons (spring, summer, autumn) in an effort to demonstrate temporal variations of three plant functional types: deciduous forest, coniferous forest, and grass. Comparisons were made for NDVI versus fAPARcanopy and for the Enhanced Vegetation Index (EVI) versus fAPARchl. In addition, EO-1 Hyperion images were utilized to simulate these new fAPARcanopy, fAPARchl, and fAPARnon\mathchar "702D chl products at 60 m as prototypes for the proposed NASA HyspIRI satellite spectrometer. These products should prove useful for future terrestrial carbon cycle and ecosystem studies. [ABSTRACT FROM PUBLISHER]

The combination of LiDAR and optical remotely sensed data provides unique information about ecosystem structure and function. Here,we describe the development,validation and application of a new airborne system that integrates commercial off the shelf LiDAR hyperspectral and thermal components in a compact,lightweight and portable system. Goddard's LiDAR,Hyperspectral and Thermal (G-LiHT) airborne imager is a unique system that permits simultaneous measurements of vegetation structure,foliar spectra and surface temperatures at very high spatial resolution (~1 m) on a wide range of airborne platforms. The complementary nature of LiDAR,optical and thermal data provide an analytical framework for the development of new algorithms to map plant species composition,plant functional types,biodiversity,biomass and carbon stocks,and plant growth. In addition,G-LiHT data enhance our ability to validate data from existing satellite missions and support NASA Earth Science research. G-LiHT's data processing and distribution system is designed to give scientists open access to both low- and high-level data products (http://gliht.gsfc.nasa.gov),which will stimulate the community development of synergistic data fusion algorithms. G-LiHT has been used to collect more than OPEN ACCESS 6,500 km2 of data for NASA-sponsored studies across a broad range of ecoregions in the USA and Mexico. In this paper,we document G-LiHT design considerations,physical specifications,instrument performance and calibration and acquisition parameters. In addition,we describe the data processing system and higher-level data products that are freely distributed under NASA's Data and Information policy. [ABSTRACT FROM AUTHOR]

We used daily MODerate resolution Imaging Spectroradiometer (MODIS) imagery obtained over a five-year period to analyze the seasonal and inter-annual variability of the fraction of absorbed photosynthetically active radiation (FAPAR) and photosynthetic light use efficiency (LUE) for the Southern Old Aspen (SOA) flux tower site located near the southern limit of the boreal forest in Saskatchewan, Canada. To obtain the spectral characteristics of a standardized land area to compare with tower measurements, we scaled up the nominal 500 m MODIS products to a 2.5 km×2.5 km area (5×5 MODIS 500 m grid cells). We then used the scaled-up MODIS products in a coupled canopy-leaf radiative transfer model, PROSAIL-2, to estimate the fraction of absorbed photosynthetically active radiation (APAR) by the part of the canopy dominated by chlorophyll (FAPARchl) versus that by the whole canopy (FAPARcanopy). Using the additional information provided by flux tower-based measurements of gross ecosystem production (GEP) and incident PAR, we determined 90-minute averages for APAR and LUE (slope of GEP:APAR) for both the physiologically active foliage (APARchl, LUEchl) and for the entire canopy (APARcanopy, LUEcanopy). The flux tower measurements of GEP were strongly related to the MODIS-derived estimates of APARchl (r 2 =0.78) but only weakly related to APARcanopy (r 2 =0.33). Gross LUE between 2001 and 2005 for LUEchl was 0.0241 µmol C µmol−1 PPFD whereas LUEcanopy was 36% lower. Time series of the 5-year normalized difference vegetation index (NDVI) were used to estimate the average length of the core growing season as days of year 152–259. Inter-annual variability in the core growing season LUEchl (µmol C µmol−1 PPFD) ranged from 0.0225 in 2003 to 0.0310 in 2004. The five-year time series of LUEchl corresponded well with both the seasonal phase and amplitude of LUE from the tower measurements but this was not the case for LUEcanopy. We conclude that LUEchl derived from MODIS observations could provide a more physiologically realistic parameter than the more commonly used LUEcanopy as an input to large-scale photosynthesis models. [Copyright &y& Elsevier]

We measured seasonal and canopy-level gas exchange in two stands of jack pine (Pinus banksiana Lamb.) and one stand of black spruce (Picea mariana (Mill.) B.S.P.) on relatively clear days from late May until mid-September 1994. Field measurements were made with a portable infrared gas analyzer, and laboratory measurements included photosynthetic oxygen evolution and needle chemical composition. Seasonally averaged light-saturated assimilation rates in the field were 4.0 μmol m−2 s−1 in jack pine and 2.7 μmol m−2 s−1 in black spruce. Rates of assimilation and transpiration were highest in midsummer. The seasonal pattern was especially pronounced for black spruce, probably because cold soil temperatures limited early season gas exchange rates in this species. Among stands, instantaneous water-use efficiency was highest in a young jack pine stand early in the season and higher in the upper canopy foliage than in the lower canopy foliage at all sites at the end of the season. Needles of young jack pine exhibited higher photosynthetic capacity, dark respiration and needle N concentrations than needles of trees at the old site. In both species, slight acclimation to shading was manifested by reductions in photosynthetic capacity in the lower canopy foliage. In both species, first-year needles had greater photosynthetic capacity than older needles but in situ rates of CO2 assimilation in the field showed little difference among needle age classes. In both species, there was a strong correlation between assimilation and stomatal conductance, indicating that assimilation was highly stomatal limited and that environmental factors that alter conductance (e.g., VPD) have a strong influence on CO2 and water fluxes, especially after early season thawing concludes. [ABSTRACT FROM AUTHOR]

There is a critical need for sensitive remote sensing approaches to monitor the parameters governing photosynthesis, at the temporal scales relevant to their natural dynamics. The photochemical reflectance index (PRI) and chlorophyll fluorescence (F) offer a strong potential for monitoring photosynthesis at local, regional, and global scales, however the relationships between photosynthesis and solar induced F (SIF) on diurnal and seasonal scales are not fully understood. This study examines how the fine spatial and temporal scale SIF observations relate to leaf level chlorophyll fluorescence metrics (i.e., PSII yield, YII and electron transport rate, ETR), canopy gross primary productivity (GPP), and PRI. The results contribute to enhancing the understanding of how SIF can be used to monitor canopy photosynthesis. This effort captured the seasonal and diurnal variation in GPP, reflectance, F, and SIF in the O2A (SIFA) and O2B (SIFB) atmospheric bands for corn (Zea mays L.) at a study site in Greenbelt, MD. Positive linear relationships of SIF to canopy GPP and to leaf ETR were documented, corroborating published reports. Our findings demonstrate that canopy SIF metrics are able to capture the dynamics in photosynthesis at both leaf and canopy levels, and show that the relationship between GPP and SIF metrics differs depending on the light conditions (i.e., above or below saturation level for photosynthesis). The sum of SIFA and SIFB (SIFA+B), as well as the SIFA+B yield, captured the dynamics in GPP and light use efficiency, suggesting the importance of including SIFB in monitoring photosynthetic function. Further efforts are required to determine if these findings will scale successfully to airborne and satellite levels, and to document the effects of data uncertainties on the scaling. [ABSTRACT FROM AUTHOR]

Solar induced chlorophyll fluorescence has been shown to be increasingly an useful proxy for the estimation of gross primary productivity (GPP), at a range of spatial scales. Here, we explore the seasonality in a continuous time series of canopy solar induced fluorescence (hereafter SiF) and its relation to canopy gross primary production (GPP), canopy light use efficiency (LUE), and direct estimates of leaf level photochemical efficiency in an evergreen canopy. SiF was calculated using infilling in two bands from the incoming and reflected radiance using a pair of Ocean Optics USB2000+ spectrometers operated in a dual field of view mode, sampling at a 30 min time step using custom written automated software, from early spring through until autumn in 2011. The optical system was mounted on a tower of 18 m height adjacent to an eddy covariance system, to observe a boreal forest ecosystem dominated by Scots pine. (Pinus sylvestris) A Walz MONITORING-PAM, multi fluorimeter system, was simultaneously mounted within the canopy adjacent to the footprint sampled by the optical system. Following correction of the SiF data for O2 and structural effects, SiF, SiF yield, LUE, the photochemicsl reflectance index (PRI), and the normalized difference vegetation index (NDVI) exhibited a seasonal pattern that followed GPP sampled by the eddy covariance system. Due to the complexities of solar azimuth and zenith angle (SZA) over the season on the SiF signal, correlations between SiF, SiF yield, GPP, and LUE were assessed on SZA <50° and under strictly clear sky conditions. Correlations found, even under these screened scenarios, resulted around ~r2 = 0.3. The diurnal responses of SiF, SiF yield, PAM estimates of effective quantum yield (ΔF/Fm′), and meteorological parameters demonstrated some agreement over the diurnal cycle. The challenges inherent in SiF retrievals in boreal evergreen ecosystems are discussed. [ABSTRACT FROM AUTHOR]

Estimates of Sun–Induced vegetation chlorophyll Fluorescence (SIF) using remote sensing techniques are commonly determined by exploiting solar and/or telluric absorption features. When SIF is retrieved in the strong oxygen (O 2 ) absorption features, atmospheric effects must always be compensated. Whereas correction of atmospheric effects is a standard airborne or satellite data processing step, there is no consensus regarding whether it is required for SIF proximal–sensing measurements nor what is the best strategy to be followed. Thus, by using simulated data, this work provides a comprehensive analysis about how atmospheric effects impact SIF estimations on proximal sensing, regarding: (1) the sensor height above the vegetated canopy; (2) the SIF retrieval technique used, e.g., Fraunhofer Line Discriminator (FLD) family or Spectral Fitting Methods (SFM); and (3) the instrument's spectral resolution. We demonstrate that for proximal–sensing scenarios compensating for atmospheric effects by simply introducing the O 2 transmittance function into the FLD or SFM formulations improves SIF estimations. However, these simplistic corrections still lead to inaccurate SIF estimations due to the multiplication of spectrally convolved atmospheric transfer functions with absorption features. Consequently, a more rigorous oxygen compensation strategy is proposed and assessed by following a classic airborne atmospheric correction scheme adapted to proximal sensing. This approach allows compensating for the O 2 absorption effects and, at the same time, convolving the high spectral resolution data according to the corresponding Instrumental Spectral Response Function (ISRF) through the use of an atmospheric radiative transfer model. Finally, due to the key role of O 2 absorption on the evaluated proximal–sensing SIF retrieval strategies, its dependency on surface pressure (p) and air temperature (T) was also assessed. As an example, we combined simulated spectral data with p and T measurements obtained for a one–year period in the Hyytiälä Forestry Field Station in Finland. Of importance hereby is that seasonal dynamics in terms of T and p, if not appropriately considered as part of the retrieval strategy, can result in erroneous SIF seasonal trends that mimic those of known dynamics for temperature–dependent physiological responses of vegetation. [ABSTRACT FROM AUTHOR]

The FLuorescence EXplorer (FLEX) satellite mission, selected as ESA's 8th Earth Explorer, has been designed for the measurement of sun-induced fluorescence ( F ) spectra emitted by plants. This will be accomplished through a multi-sensor approach by placing it in a common orbit in tandem with the Sentinel-3 (S3) mission, which will have two optical sensors on board, OLCI (Ocean and Land Colour Instrument) and SLSTR (Sea and Land Surface Temperature Radiometer) to complement FLEX. These S3 instruments will be used in combination with the imaging spectrometers on board FLEX to provide data useful for atmospheric correction of FLEX data. However, a fully synergetic approach, i.e. by exploiting the spectral and directional information from all tandem mission instruments together, is an attractive alternative which is explored in this paper. By employing all combined top-of-atmosphere (TOA) spectral radiance data, one can (i) characterize the relevant optical properties of the atmosphere, (ii) retrieve biophysical canopy properties including the associated reflectance anisotropy, and (iii) retrieve a more accurate and consistent canopy F . Regarding retrieval methods, Fraunhofer Line Depth (FLD) and Spectral Fitting (SF) are well-known techniques applied to hyperspectral data. Both methods depend on a high spectral resolution and assume a Lambertian (isotropic) canopy reflectance. However, most vegetation canopies are non-Lambertian. This implies that, in particular when ignoring the anisotropic surface reflection, substantial retrieval errors can occur due to the interaction between atmospheric absorption bands and surface reflectance anisotropy. In this paper, a novel method based on spectral radiative transfer (RT) modeling is proposed, in which coupled RT models are used to simulate TOA radiance spectra. These are then matched with ‘measured’ spectra in order to retrieve surface fluorescence, along with a suite of biophysical parameters, by model inversion through optimization. By applying coupled RT models of the soil-leaf-canopy and the surface-atmosphere systems, TOA radiance spectra can be simulated for all optical sensors of this tandem mission. In this way, complex effects due to surface reflectance anisotropy and the spectral sampling by the various instruments, which are difficult to compensate for in the end products, are properly taken into account by their incorporation in the forward modeling. Next, by model inversion of TOA radiance data via optimization, the most accurate F retrievals can be achieved in a consistent manner, along with important canopy level biophysical parameters that may help interpret the F spectrum, such as chlorophyll content and leaf area index (LAI). The potential of this approach has been explored in a numerical experiment, and the results are presented in this paper. We find that, with the assumed well-characterized and plausible FLEX/S3 instrument performances, the simultaneous retrieval of biophysical canopy parameters and F spectra would be possible with a remarkable accuracy, provided the correct atmospheric characterization is available. [ABSTRACT FROM AUTHOR]

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

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R² = 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R² > 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology. [ABSTRACT FROM AUTHOR]

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