Fraction Of Absorbed Photosynthetically Active Radiation Products Research Articles

Improving Satellite Estimates of the Fraction of Absorbed Photosynthetically Active Radiation Through Data Integration: Methodology and Validation

The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical input in many climate and ecological models. The accuracy of satellite FAPAR products directly influences estimates of ecosystem productivity and carbon stocks. The targeted accuracy of FAPAR products is 10% or 0.05 for many applications. However, most current FAPAR products do not meet such requirements, and further improvements are still needed. In this paper, a data fusion scheme based on the multiple resolution tree (MRT) approach is developed to integrate multiple satellite FAPAR estimates at site and regional scales. MRT was chosen because of the superior computational efficiency compared with other fusion methods. The fusion scheme removed the bias in FAPAR estimates and resulted in a 15% increase in the $R^{2}$ and 3% reduction in the root-mean-square error compared with the average of individual FAPAR estimates. The regional-scale fusion filled in the missing values, and provided spatially consistent FAPAR distributions at different resolutions. Overall, MRT can be used to efficiently and accurately generate spatially and temporally continuous FAPAR data across both site and regional scales.

Estimation of FAPAR over Croplands Using MISR Data and the Earth Observation Land Data Assimilation System (EO-LDAS)

The Fraction of Absorbed Photosynthetically-Active Radiation (FAPAR) is an important parameter in climate and carbon cycle studies. In this paper, we use the Earth Observation Land Data Assimilation System (EO-LDAS) framework to retrieve FAPAR from observations of directional surface reflectance measurements from the Multi-angle Imaging SpectroRadiometer(MISR) instrument. The procedure works by interpreting the reflectance data via the semi-discrete Radiative Transfer (RT) model, supported by a prior parameter distribution and a dynamic regularisation model and resulting in an inference of land surface parameters, such as effective Leaf Area Index (LAI), leaf chlorophyll concentration and fraction of senescent leaves, with full uncertainty quantification. The method is demonstrated over three agricultural FLUXNET sites, and the EO-LDAS results are compared with eight years of in situ measurements of FAPAR and LAI, resulting in a total of 24 site years. We additionally compare three other widely-used EO FAPAR products, namely the MEdium Resolution Imaging Spectrometer (MERIS) Full Resolution, the MISR High Resolution (HR) Joint Research Centre Two-stream Inversion Package (JRC-TIP) and MODIS MCD15 FAPAR products. The EO-LDAS MISR FAPAR retrievals show a high correlation with the ground measurements ( r 2 > 0.8), as well as the lowest average R M S E (0.14), in line with the MODIS product. As the EO-LDAS solution is effectively interpolated, if only measurements that are coincident with MISR observations are considered, the correlation increases ( r 2 > 0.85); the R M S E is lower by 4–5%; and the bias is 2% and 7%. The EO-LDAS MISR LAI estimates show a strong correlation with ground-based LAI (average r 2 = 0.76), but an underestimate of LAI for optically-thick canopies due to saturation (average R M S E = 2.23). These results suggest that the EO-LDAS approach is successful in retrieving both FAPAR and other land surface parameters. A large part of this success is based on the use of a dynamic regularisation model that counteracts the poor temporal sampling from the MISR instrument.

Estimation of fraction of absorbed photosynthetically active radiation from multiple satellite data: Model development and validation

Abstract The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical input in numerous climatological and ecological models. The targeted accuracy of FAPAR products is 10%, or 0.05, for many applications. However, most of the FAPAR products in current usage have not yet fulfilled the accuracy requirement, thus requiring further improvements. In this study, a new FAPAR estimation model is developed on the basis of the radiative transfer (RT) for a horizontally homogeneous continuous canopy. The spatially explicit parameterization of leaf-scattering and soil background reflectance is derived from a 13-year Moderate Resolution Imaging Spectroradiometer (MODIS) albedo database. The new algorithm requires the input of leaf area index (LAI), which is estimated by a hybrid geometric optical-RT model suitable for both continuous and discrete vegetation canopies in this study. The model calculated radiative surface fluxes, i.e., canopy reflectance, absorption, and transmittance, are compared with the reference data from Radiation transfer Model Intercomparison (RAMI) exercise. The evaluation results show that the model estimated FAPAR has an uncertainty of 0.08 over homogeneous and heterogeneous canopies. The FAPAR estimates from the new model are intercompared with reference satellite FAPAR products and validated with ground-based measurements at the Validation of Land European Remote Sensing Instruments (VALERI) AmeriFlux experimental sites. The validation results show that the FAPAR estimates from the new model are comparable to or slightly better in performance than the MODIS and the Multi-angle Imaging SpectroRadiometer (MISR) FAPAR products when using corresponding satellite LAI product values as the input. The FAPAR estimates are further improved when using the new LAI estimates from the hybrid model as the input. The new model adequately identifies the growing seasons and produces smooth time series curves of estimated FAPAR during a specific duration. The uncertainty is reduced to 0.1 when validating with total FAPAR measurements, and 0.08 when validating with green FAPAR measurements. The improvements are apparent in grasslands and forests with an uncertainty reduction of 0.06. The regional-scale application of the presented model generates consistent FAPAR maps at spatial resolutions of 30 m, 500 m, and 1 km from the Landsat, MODIS, and MISR data, respectively.

Retrieval of Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from VIIRS Time-Series Data

Long-term high-quality global leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR) products are urgently needed for the study of global change, climate modeling, and many other problems. As the successor of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) will continue to provide global environmental measurements. This paper aims to generate longer time series Global LAnd Surface Satellite (GLASS) LAI and FAPAR products after the era of the MODIS sensor. To ensure spatial and temporal consistencies between GLASS LAI/FAPAR values retrieved from different satellite observations, the GLASS LAI/FAPAR retrieval algorithms were adapted in this study to retrieve LAI and FAPAR values from VIIRS surface reflectance time-series data. After reprocessing of the VIIRS surface reflectance to remove remaining effects of cloud contamination and other factors, a database generated from the GLASS LAI product and the reprocessed VIIRS surface reflectance for all Benchmark Land Multisite Analysis and Intercomparison of Products (BELMANIP) sites was used to train general regression neural networks (GRNNs). The reprocessed VIIRS surface reflectance data from an entire year were entered into the trained GRNNs to estimate the one-year LAI values, which were then used to calculate FAPAR values. A cross-comparison indicates that the LAI and FAPAR values retrieved from VIIRS surface reflectance were generally consistent with the GLASS, MODIS and Geoland2/BioPar version 1 (GEOV1) LAI/FAPAR values in their spatial patterns. The LAI/FAPAR values retrieved from VIIRS surface reflectance achieved good agreement with the GLASS LAI/FAPAR values (R2 = 0.8972 and RMSE = 0.3054; and R2 = 0.9067 and RMSE = 0.0529, respectively). However, validation of the LAI and FAPAR values derived from VIIRS reflectance data is now limited by the scarcity of LAI/FAPAR ground measurements.

Scaling of FAPAR from the Field to the Satellite

The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical biophysical parameter in eco-environmental studies. Scaling of FAPAR from the field observation to the satellite pixel is essential for validating remote sensing FAPAR product and for further modeling applications. However, compared to spatial mismatches, few studies have considered temporal mismatches between in-situ and satellite observations in the scaling. This paper proposed a general methodology for scaling FAPAR from the field to the satellite pixel considering the temporal variation. Firstly, a temporal normalization method was proposed to normalize the in-situ data measured at different times to the time of satellite overpass. The method was derived from the integration of an atmospheric radiative transfer model (6S) and a FAPAR analytical model (FAPAR-P), which can characterize the diurnal variations of FAPAR comprehensively. Secondly, the logistic model, which derives smooth and consistent temporal profile for vegetation growth, was used to interpolate the in-situ data to match the dates of satellite acquisitions. Thirdly, fine-resolution FAPAR products at different dates were estimated from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data using the temporally corrected in-situ data. Finally, fine-resolution FAPAR were taken as reference datasets and aggregated to coarse resolution, which were further compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) FAPAR product. The methodology is validated for scaling FAPAR from the field to the satellite pixel temporally and spatially. The MODIS FAPAR manifested a good consistency with the aggregated FAPAR with R2 of 0.922 and the root mean squared error of 0.054.

Assessing the Impact of Climate Variability on Cropland Productivity in the Canadian Prairies Using Time Series MODIS FAPAR

Cropland productivity is impacted by climate. Knowledge on spatial-temporal patterns of the impacts at the regional scale is extremely important for improving crop management under limiting climatic factors. The aim of this study was to investigate the effects of climate variability on cropland productivity in the Canadian Prairies between 2000 and 2013 based on time series of MODIS (Moderate Resolution Imaging Spectroradiometer) FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) product. Key phenological metrics, including the start (SOS) and end of growing season (EOS), and the cumulative FAPAR (CFAPAR) during the growing season (between SOS and EOS), were extracted and calculated from the FAPAR time series with the Parametric Double Hyperbolic Tangent (PDHT) method. The Mann-Kendall test was employed to assess the trends of cropland productivity and climatic variables, and partial correlation analysis was conducted to explore the potential links between climate variability and cropland productivity. An assessment using crop yield statistical data showed that CFAPAR can be taken as a surrogate of cropland productivity in the Canadian Prairies. Cropland productivity showed an increasing trend in most areas of Canadian Prairies, in general, during the period from 2000 to 2013. Interannual variability in cropland productivity on the Canadian Prairies was influenced positively by rainfall variation and negatively by mean air temperature.

Estimating the fraction of absorbed photosynthetically active radiation from the MODIS data based GLASS leaf area index product

Abstract The fraction of absorbed photosynthetically active radiation (FAPAR) is an essential biophysical variable and plays a critical role in the carbon cycle. Existing FAPAR products from satellite observations are spatially incomplete and temporally discontinuous, and also insufficiently accurate to meet the requirements of various applications. In this study, a new method is proposed to calculate high quality, accurate FAPAR from the Global LAnd Surface Satellite (GLASS) leaf area index (LAI) to ensure physical consistency between LAI and FAPAR retrievals. As a result, a global FAPAR product (denoted by GLASS) was generated from the GLASS LAI data from 2000. With no missing values, GLASS FAPAR product is spatially complete. Comparison of the GLASS FAPAR product with the MODerate Resolution Imaging Spectroradiometer (MODIS), Geoland2/BioPar version 1 (GEOV1), and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) FAPAR products indicates that these FAPAR products exhibit similar spatial distribution pattern. However, there were relatively large discrepancies between these FAPAR products in equatorial forest regions and around 50–60°N, where the SeaWiFS FAPAR values were lower than the other products and GLASS FAPAR product showed the largest values. Temporal consistency analysis indicates that GLASS FAPAR product has continuous trajectories, while MODIS FAPAR product shows more unstable profiles, especially during the growing season. Direct comparison with ground-based estimates demonstrated that GLASS FAPAR values were more accurate (R 2 = 0.9292 and RMSE = 0.0716) than GEOV1 (R 2 = 0.8681 and RMSE = 0.1085), MODIS (R 2 = 0.8048 and RMSE = 0.1276) and SeaWiFS FAPAR values (R 2 = 0.7377 and RMSE = 0.1635).

A New Algorithm of the FPAR Product in the Heihe River Basin Considering the Contributions of Direct and Diffuse Solar Radiation Separately

It remains a challenging issue to accurately estimate the fraction of absorbed photosynthetically-active radiation (FPAR) using remote sensing data, as the direct and diffuse radiation reaching the vegetation canopy have different effects for FPAR. In this research, a FPAR inversion model was developed that may distinguish direct and diffuse radiation (the DnD model) based on the energy budget balance principle. Taking different solar zenith angles and diffuse PAR proportions as inputs, the instantaneous FPAR could be calculated. As the leaf area index (LAI) and surface albedo do not vary in a short periods, the FPAR not only on a clear day, but also on a cloudy day may be calculated. This new method was used to produce the FPAR products in the Heihe River Basin with the Moderate-Resolution Imaging Spectroradiometer (MODIS) LAI and surface albedo products as the input data source. The instantaneous FPAR was validated by using field-measured data (RMSE is 0.03, R2 is 0.85). The daily average FPAR was compared with the MODIS FPAR product. The inversion results and the MODIS FPAR product are highly correlated, but the MODIS FPAR product is slightly high in forest areas, which is in agreement with other studies for MODIS FPAR products.

Early validation of PROBA-V GEOV1 LAI, FAPAR and FCOVER products for the continuity of the Copernicus Global Land Service

Abstract. This study investigates the scientific quality of the GEOV1 Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and Fraction of Vegetation Cover (FCover) products based on PROBA-V observations. The procedure follows, as much as possible, the guidelines, protocols and metrics defined by the Land Product Validation (LPV) group of the Committee on Earth Observation Satellite (CEOS) for the validation of satellite-derived land products. This study is focused on the consistency of SPOT/VGT and PROBA-V GEOV1 products developed in the framework of the Copernicus Global Land Services, providing an early validation of PROBA-V GEOV1 products using data from November 2013 to May 2014, during the overlap period (November 2013-May 2014). The first natural year of PROBA-V GEOV1 products (2014) was considered for the rest of the quality assessment including comparisons with MODIS C5. Several criteria of performance were evaluated including product completeness, spatial consistency, temporal consistency, intra-annual precision and accuracy. Firstly, and inter-comparison with both spatial and temporal consistency were evaluated with reference satellite products (SPOT/VGT GEOV1 and MODIS C5) are presented over a network of sites (BELMANIP2.1). Secondly, the accuracy of PROBA-V GEOV1 products was evaluated against a number of concomitant agricultural sites is presented. The ground data was collected and up-scaled using high resolution imagery in the context of the FP7 ImagineS project in support of the evolution of Copernicus Land Service. Our results demonstrate that GEOV1 PROBA-V products were found spatially and temporally consistent with similar products (SPOT/VGT, MODISC5), and good agreement with limited ground truth data with an accuracy (RMSE) of 0.52 for LAI, 0.11 for FAPAR and 0.14 for FCover, showing a slight bias for FCover for higher values.

Modelling the Gross Primary Productivity of West Africa with the Regional Biomass Model RBM+, using optimized 250 m MODIS FPAR and fractional vegetation cover information

Global warming associated with climate change is one of the greatest challenges of today’s world. Increasing emissions of the greenhouse gas CO2 are considered as a major contributing factor to global warming. One regulating factor of CO2 exchange between atmosphere and land surface is vegetation. Measurements of land cover changes in combination with modelling the Gross Primary Productivity (GPP) can contribute to determine important sources and sinks of CO2.The aim of this study is to accurately model the GPP for a region in West Africa with a spatial resolution of 250m, and the differentiation of GPP based on woody and herbaceous vegetation. For this purpose, the Regional Biomass Model (RBM) was applied, which is based on a Light Use Efficiency (LUE) approach. The focus was on the spatial enhancement of the RBM from the original 1000–250m spatial resolution (RBM+). The adaptation to the 250m scale included the modification of two main input parameters: (1) the fraction of absorbed Photosynthetically Active Radiation (FPAR) based on the 1000m MODIS MOD15A2 FPAR product which was downscaled to 250m using MODIS NDVI time series; (2) the fractional cover of woody and herbaceous vegetation, which was improved by using a multi-scale approach. For validation and regional adjustments of GPP and the input parameters, in situ data from a climate station and eddy covariance measurements were integrated.The results of this approach show that the input parameters could be improved significantly: downscaling considerably reduces data gaps of the original FPAR product and the improved dataset differed less than 5.0% from the original data for cloud free regions. The RMSE of the fractional vegetation cover varied between 5.1 and 12.7%. Modelled GPP showed a slight overestimation in comparison to eddy covariance measurements. The in situ data was exceeded by 8.8% for 2005 and by 2.0% for 2006. The model results were converted to NPP and also agreed well with previous NPP measurements reported from different studies. Altogether a high accuracy and suitability of the regionally adjusted and downscaled model RBM+ can be concluded. The differentiation between vegetation growth forms allows a separation of long-term and short-term carbon storage based on woody and herbaceous vegetation, respectively.

Assessment of five global satellite products of fraction of absorbed photosynthetically active radiation: Intercomparison and direct validation against ground-based data

The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical input parameter in many climate and ecological models. The accuracy of satellite FAPAR products directly influences estimates of ecosystem productivity and carbon stocks. The targeted accuracy of FAPAR products is 10%, or 0.05, for many applications. It is important to evaluate satellite FAPAR products and understand differences between the products to effectively use them in carbon cycling models. In this study, five global FAPAR products, namely MODIS, MISR, MERIS, SeaWiFS, and GEOV1 are intercompared over different land covers and directly validated with ground-based measurements at VAlidation of Land European Remote sensing Instruments (VALERI) and AmeriFlux sites. Intercomparison results show that MODIS, MISR, and GEOV1 agree well with each other and so do MERIS and SeaWiFS, but the difference between these two groups can be as large as 0.1. The temporal trends of these products agree better with each other in the Northern Hemisphere than in the Southern Hemisphere. The trends in the Northern Hemisphere are similar to those globally. However, the conclusions from the northern hemispheric scale could not be extended to the global scale for land covers such as savannahs and broadleaf evergreen forests. The differences between the products are consistent throughout the year over most of the land cover types, except over the forests, because of the different assumptions in the retrieval algorithms and the differences between green and total FAPAR products over forests. Direct validation results show that MERIS, MODIS, MISR, and GEOV1 FAPAR products have an uncertainty of 0.14 when validating with total FAPAR measurements, and 0.09 when validating with green FAPAR measurements. Overall, current FAPAR products are close to, but have not fulfilled, the accuracy requirement, and further improvements are still needed.

A New FAPAR Analytical Model Based on the Law of Energy Conservation: A Case Study in China

The fraction of absorbed photosynthetically active radiation (FAPAR) characterizes the energy-absorption ability of the vegetation canopy. It is a critical input to many land-surface models such as crop growth models, net primary productivity models, and climate models. There is a great need for FAPAR products derived from remote-sensing data. The objective of this research is to develop a new instantaneous quantitative FAPAR model based on the law of energy conservation and the concept of recollision probability (p). Using the ray-tracing method, the FAPAR-P model separates direct energy absorption by the canopy from energy absorption caused by multiple scattering between the soil and the canopy. Direct sunlight and diffuse skylight are also considered. This model has a clear physical meaning and can be applied to continuous and discrete vegetation. The model was validated by Monte Carlo (MC) simulation and field measurements in the Heihe River basin, China, which proved its reliability for FAPAR calculations.

Validation of MERIS LAI and FAPAR products for winter wheat-sown test fields in North-East Bulgaria

Progress in deriving land surface biophysical parameters in a spatially explicit manner using remotely sensed data has greatly enhanced our ability to model ecosystem processes and monitor crop development. A multitude of satellite sensors and algorithms have been used to generate ready-to-use maps of various biophysical parameters. Validation of these products for different vegetation types is needed to assess their reliability and consistency. While most of the current satellite biophysical products have spatial resolution of one kilometre, a recent effort utilizing data from the Medium Resolution Imaging Spectrometer (MERIS) provided leaf area index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and other canopy parameters in a resolution as fine as 300 m over the European continent. This resolution would be more appropriate for application at the regional scale, particularly for crop monitoring. This higher-resolution MERIS product has been evaluated in a limited number of studies to date. This article aims to validate LAI and FAPAR from the MERIS 10-day composite BioPar BP-10 product over winter wheat fields in northeast Bulgaria. The ground measurements of LAI and FAPAR were up-scaled and 30 m resolution reference raster layers were created using empirical relationships with Landsat TM (RMSE = 0.06 and RMSE = 0.22 for FAPAR and LAI, respectively). MERIS FAPAR and LAI were found to have significant correlation with FAPAR and LAI from the reference raster layers (R2 = 0.84 and R2 = 0.78, respectively). When MERIS Green LAI was calculated (incorporating the fraction of vegetation and brown vegetation cover from the BioPar BP-10 product), better correspondence with LAI values from the reference raster layer was achieved, with RMSE and bias reduced by 30–35%. The results from this study confirm the findings of previous validations showing that MERIS Green LAI tends to overestimate LAI values lower than 1. As a conclusion of the study, the BioPar BP-10 product was found to provide reliable estimates of FAPAR and acceptably accurate estimates of LAI for winter wheat crops in North-East Bulgaria.

On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products

The OLIVE (On Line Interactive Validation Exercise) platform is dedicated to the validation of global biophysical products such as LAI (Leaf Area Index) and FAPAR (Fraction of Absorbed Photosynthetically Active Radiation). It was developed under the framework of the CEOS (Committee on Earth Observation Satellites) Land Product Validation (LPV) sub-group. OLIVE has three main objectives: (i) to provide a consistent and centralized information on the definition of the biophysical variables, as well as a description of the main available products and their performances (ii) to provide transparency and traceability by an online validation procedure compliant with the CEOS LPV and QA4EO (Quality Assurance for Earth Observation) recommendations (iii) and finally, to provide a tool to benchmark new products, update product validation results and host new ground measurement sites for accuracy assessment. The functionalities and algorithms of OLIVE are described to provide full transparency of its procedures to the community. The validation process and typical results are illustrated for three FAPAR products: GEOV1 (VEGETATION sensor), MGVIo (MERIS sensor) and MODIS collection 5 FPAR. OLIVE is available on the European Space Agency CAL/VAL portal), including full documentation, validation exercise results, and product extracts.

Yield estimation using SPOT-VEGETATION products: A case study of wheat in European countries

In the period 1999–2009 ten-day SPOT-VEGETATION products of the Normalized Difference Vegetation Index (NDVI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) at 1km spatial resolution were used in order to estimate and forecast the wheat yield over Europe. The products were used together with official wheat yield statistics to fine-tune a statistical model for each NUTS2 region, based on the Partial Least Squares Regression (PLSR) method. This method has been chosen to construct the model in the presence of many correlated predictor variables (10-day values of remote sensing indicators) and a limited number of wheat yield observations. The model was run in two different modalities: the “monitoring mode”, which allows for an overall yield assessment at the end of the growing season, and the “forecasting mode”, which provides early and timely yield estimates when the growing season is on-going. Performances of yield estimation at the regional and national level were evaluated using a cross-validation technique against yield statistics and the estimations were compared with those of a reference crop growth model. Models based on either NDVI or FAPAR normalized indicators achieved similar results with a minimal advantage of the model based on the FAPAR product. Best modelling results were obtained for the countries in Central Europe (Poland, North-Eastern Germany) and also Great Britain. By contrast, poor model performances characterize countries as follows: Sweden, Finland, Ireland, Portugal, Romania and Hungary. Country level yield estimates using the PLSR model in the monitoring mode, and those of a reference crop growth model that do not make use of remote sensing information showed comparable accuracies. The largest estimation errors were observed in Portugal, Spain and Finland for both approaches. This convergence may indicate poor reliability of the official yield statistics in these countries.

Intercomparison of fraction of absorbed photosynthetically active radiation products derived from satellite data over Europe

The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is recognized as an essential climate variable (ECVs), playing a critical role in the estimation of the global energy and carbon balance. With multiple space-borne remote sensing FAPAR global products available from several sources the need for continual comparison and validation has become imperative. In this study, the performance of three global FAPAR algorithms (JRC-TIP, ESA/JRC MGVI and Boston University FAPAR) was evaluated over Europe for the year 2011. Results show an overall agreement among FAPAR products on sites having high and low FAPAR values, except for the north-eastern region of Europe characterized by boreal forest and the transition region with tundra biomes, where the Boston product exceeds values in other products by up to 0.5. Differences in FAPAR estimates over forest biomes suggest that assumptions on structure and optical properties of land surfaces in the different radiative transfer models play an important role in remote-sensing-derived FAPAR products. Uncertainty assessments were carried out using both quality indicators as proposed by the individual product teams as well as independent theoretical uncertainty estimates obtained with the triple collocation error model. The former revealed consistent spatial patterns but large differences in magnitudes (up to 0.1) with systematically lower uncertainties for the Boston product. The latter instead suggests similar uncertainty ranges among the three products. Finally, a comparison with ground estimates for the 2009–2011 period over four European flux tower sites showed consistent, plausible seasonal variations of remote-sensing-derived FAPAR products. Findings suggest that differences in absolute values and inconsistency in uncertainty representation among FAPAR products are still considerable. Standardization frameworks quantifying the impact of different radiative transfer formulations on the estimation of biophysical variables, independent uncertainty estimation methods and well-defined ground measurement protocols need to be put in place before FAPAR products can be reliably fed into existing biogeochemical process models.

Evaluation of the influence of two operational fraction of absorbed photosynthetically active radiation (FAPAR) products on terrestrial ecosystem productivity modelling

The fraction of photosynthetically active radiation absorbed by vegetation (FAPAR) represents the available light energy for plant productivity and is the key variable influencing photosynthesis, transpiration, and energy balance in most terrestrial vegetation productivity models. With availability of earth observation data from different satellite sensors increasing, a number of FAPAR products are being generated. Several studies have investigated the differences between these products. However, very few studies have investigated how the differences between these products influence the output from ecosystem productivity models that utilise them. This study evaluated the influence of two operational FAPAR products (i.e. the MODIS and CYCLOPES FAPAR products) on the terrestrial vegetation primary productivity predicted by the Carnegie–CASA model across various biomes in the USA. The GPP predicted by the Carnegie–CASA model was compared to GPP measurements from various flux tower sites representing five biomes (i.e. croplands, broadleaf deciduous forests, grassland, needle-leaf evergreen forests, and savanna woodland). With the exception of cropland sites, the two FAPAR products resulted in GPP predictions which were higher than the in situ GPP measurements for the evaluated biomes. However, the CYCLOPES FAPAR product resulted in GPP outputs which were closer (lower RMSE values) to the in situ measurements than the MODIS FAPAR product. The two FAPAR products do not account for the FAPAR absorbed by non-photosynthetic elements of the canopy, which may lead to overestimation of the FAPAR that is actually used in photosynthesis. This could explain the higher GPP values derived using these products when compared to the in situ GPP measurements.

Validation of coarse spatial resolution LAI and FAPAR time series over cropland in southwest France

This study aims at validating Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) products derived from MODIS surface reflectance (MOD09CMG) at coarse resolution (0.05°) over crops. These Essential Climate Variables (ECVs) are estimated by using the inversion of the PROSAIL radiative transfer (BV-NNET tool) applied on MODIS BRDF (Bidirectional Reflectance Distribution Function) corrected surface reflectances and non-corrected. ECV estimates and the corresponding MCD15A3 Collection 5 and GEOLAND-2 (GEOv1) products are compared with ECV reference maps derived from BV-NNET applied on 105 high spatial resolution images (Formosat-2, 8m) which were acquired from 2006 to 2010 in Southwest France. These latter are compared with local scale in situ measurements. The validation shows an uncertainty of 0.35 and 0.07 for LAI and FAPAR, respectively.The comparison shows that the ECV estimates from the three products properly capture the crops phenology in agreement with reference maps. Results indicate that MCD15A3 uncertainties (0.23 and 0.07 for LAI and FAPAR, respectively) are similar to previous intercomparison studies. GEOv1 shows a systemic positive bias for both LAI and FAPAR. The best agreement with the reference maps is found for MODIS BV-NNET products with r2 higher than 0.9 and relative uncertainties lower than 17%. The use of BRDF-corrected surface reflectances as input of BV-NNET tool improves the uncertainty of LAI estimates (0.11, compared to 0.17 when directional surface reflectances are used as input) but not the uncertainty of FAPAR estimates. The deviation between FAPAR products which mostly affects low winter FAPAR, is related to the discrepancy of the soil directional assumption in PROSAIL model and BRDF correction method. The temporal stability of the daily MODIS BV-NNET products is better than the 4-day composite MCD15A3 products. Finally, BV-NNET tool applied at finer resolutions demonstrates that the increase of the resolution results in a decrease of the LAI and FAPAR uncertainties and a conservation of the biases.

An algorithm to derive the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (FAPARps) from eddy covariance flux tower data

The fraction of absorbed photosynthetically active radiation (FAPAR) is a key vegetation biophysical variable in most production efficiency models (PEMs). Operational FAPAR products derived from satellite data do not distinguish between the fraction of photosynthetically active radiation (PAR) absorbed by nonphotosynthetic and photosynthetic components of vegetation canopy, which would result in errors in representation of the exact absorbed PAR utilized in photosynthesis. The possibility of deriving only the fraction of PAR absorbed by photosynthetic elements of the canopy (i.e. FAPAR(ps) ) was investigated. The approach adopted involved inversion of net ecosystem exchange data from eddy covariance measurements to calculate FAPAR(ps) . The derived FAPAR(ps) was then related to three vegetation indices (i.e. Normalized Difference Vegetation Index (NDVI), Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) and Enhanced Vegetation Index (EVI)) in an attempt to determine their potential as surrogates for FAPAR(ps) . Finally, the FAPAR(ps) was evaluated against two operational satellite data-derived FAPAR products (i.e. MODIS and CYCLOPES products). The maximum FAPAR(ps) from the inversion approach ranged between 0.6 and 0.8. The inversion approach also predicted site-specific Q₁₀-modelled daytime respiration successfully (R² > 0.8). The vegetation indices were positively correlated (R² = 0.67-0.88) to the FAPAR(ps). Finally, the two operational FAPAR products overestimated the FAPAR(ps). This was attributed to the two products deriving FAPAR for the whole canopy rather than for only photosynthetic elements in the canopy.

Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula

The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences are found over the Iberian Peninsula concentrated on the temporal variation and absolute values. The MODIS and MERIS/MGVI FAPAR products clearly show the highest and lowest absolute values, respectively, along with the lowest intra-annual variation. When considering individual land cover types, the largest FAPAR disagreements among the analyzed products were found between MODIS-MERI/MGVI and MERIS/TOAVEG-MERIS/MGVI over broadleaf and needleaf forests, with discrepancies quantified by RMSE higher than 0.30 and absolute bias higher than 0.25. These discrepancies can lead to relative gross primary production differences up to 65%.