A New Global fAPAR and LAI Dataset Derived from Optimal Albedo Estimates: Comparison with MODIS Products

Upscaling from Instantaneous to Daily Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) for Satellite Products

The fraction of absorbed photosynthetically active radiation (FAPAR) is an essential climate variable (ECV) widely used for various ecological and climate models. However, all the current FAPAR satellite products correspond to instantaneous FAPAR values acquired at the satellite transit time only, which cannot represent the variations in photosynthetic processes over the diurnal period. Most studies have directly used the instantaneous FAPAR as a reasonable approximation of the daily integrated value. However, clearly, FAPAR varies a lot according to the weather conditions and amount of incoming radiation. In this paper, a temporal upscaling method based on the cosine of the solar zenith angle (SZA) at local noon ( c o s ( S Z A n o o n ) ) is proposed for converting instantaneous FAPAR to daily integrated FAPAR. First, the diurnal variations in FAPAR were investigated using PROSAIL (a model of Leaf Optical Properties Spectra (PROSPECT) integrating a canopy radiative transfer model (Scattering from Arbitrarily Inclined Leaves, SAIL)) simulations with different leaf area index (LAI) values corresponding to different latitudes. It was found that the instantaneous black sky FAPAR at 09:30 AM provided a good approximation for the daily integrated black sky FAPAR; this gave the highest correlation (R2 = 0.995) and lowest Root Mean Square Error (RMSE = 0.013) among the instantaneous black sky FAPAR values observed at different times. Secondly, the difference between the instantaneous black sky FAPAR values acquired at different times and the daily integrated black sky FAPAR was analyzed; this could be accurately modelled using the cosine value of solar zenith angle at local noon ( c o s ( S Z A n o o n ) ) for a given vegetation scene. Therefore, a temporal upscaling method for typical satellite products was proposed using a cos(SZA)-based upscaling model. Finally, the proposed cos(SZA)-based upscaling model was validated using both the PROSAIL simulated data and the field measurements. The validated results indicated that the upscaled daily black sky FAPAR was highly consistent with the daily integrated black sky FAPAR, giving very high mean R2 values (0.998, 0.972), low RMSEs (0.007, 0.014), and low rMAEs (0.596%, 1.378%) for the simulations and the field measurements, respectively. Consequently, the cos(SZA)-based method performs well for upscaling the instantaneous black sky FAPAR to its daily value, which is a simple but extremely important approach for satellite remote sensing applications related to FAPAR.

Can We Use the QA4ECV Black-sky Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) using AVHRR Surface Reflectance to Assess Terrestrial Global Change?

NOAA platforms provide the longest period of terrestrial observation since the 1980s. The progress in calibration, atmospheric corrections and physically based land retrieval offers the opportunity to reprocess these data for extending terrestrial product time series. Within the Quality Assurance for Essential Climate Variables (QA4ECV) project, the black-sky Joint Research Centre (JRC)-fraction of absorbed photosynthetically active radiation (FAPAR) algorithm was developed for the AVHRR sensors on-board NOAA-07 to -16 using the Land Surface Reflectance Climate Data Record. The retrieval algorithm was based on the radiative transfer theory, and uncertainties were included in the products. We proposed a time and spatial composite for providing both 10-day and monthly products at 0.05º × 0.05º. Quality control and validation were achieved through benchmarking against third-party products, including Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) datasets produced with the same retrieval algorithm. Past ground-based measurements, providing a proxy of FAPAR, showed good agreement of seasonality values over short homogeneous canopies and mixed vegetation. The average difference between SeaWiFS and QA4ECV monthly products over 2002–2005 is about 0.075 with a standard deviation of 0.091. We proposed a monthly linear bias correction that reduced these statistics to 0.02 and 0.001. The complete harmonized long-term time series was then used to address its fitness for the purpose of analysis of global terrestrial change.

Retrieval of the Fraction of Radiation Absorbed by Photosynthetic Components (FAPARgreen) for Forest using a Triple-Source Leaf-Wood-Soil Layer Approach

The fraction of absorbed photosynthetically active radiation (FAPAR) is generally divided into the fraction of radiation absorbed by the photosynthetic components (FAPARgreen) and the fraction of radiation absorbed by the non-photosynthetic components (FAPARwoody) of the vegetation. However, most global FAPAR datasets do not take account of the woody components when considering the canopy radiation transfer. The objective of this study was to develop a generic algorithm for partitioning FAPARcanopy into FAPARgreen and FAPARwoody based on a triple-source leaf-wood-soil layer (TriLay) approach. The LargE-Scale remote sensing data and image simulation framework (LESS) model was used to validate the TriLay approach. The results showed that the TriLay FAPARgreen had higher retrieval accuracy, as well as a significantly lower bias (R2 = 0.937, Root Mean Square Error (RMSE) = 0.064, and bias = −6.02% for black-sky conditions; R2 = 0.997, RMSE = 0.025 and bias = −4.04% for white-sky conditions) compared to the traditional linear method (R2 = 0.979, RMSE = 0.114, and bias = −18.04% for black-sky conditions; R2 = 0.996, RMSE = 0.106 and bias = −16.93% for white-sky conditions). For FAPAR that did not take account of woody components (FAPARnoWAI), the corresponding results were R2 = 0.920, RMSE = 0.071, and bias = −7.14% for black-sky conditions, and R2 = 0.999, RMSE = 0.043, and bias = −6.41% for white-sky conditions. Finally, the dynamic FAPARgreen, FAPARwoody, FAPARcanopy and FAPARnoWAI products for a North America region were generated at a resolution of 500 m for every eight days in 2017. A comparison of the results for FAPARgreen against those for FAPARnoWAI and FAPARcanopy showed that the discrepancy between FAPARgreen and other FAPAR products for forest vegetation types could not be ignored. For deciduous needleleaf forest, in particular, the black-sky FAPARgreen was found to contribute only about 23.86% and 35.75% of FAPARcanopy at the beginning and end of the year (from January to March and October to December, JFM and OND), and 75.02% at the peak growth stage (from July to September, JAS); the black-sky FAPARnoWAI was found to be overestimated by 38.30% and 28.46% during the early (JFM) and late (OND) part of the year, respectively. Therefore, the TriLay approach performed well in separating FAPARgreen from FAPARcanopy, which is of great importance for a better understanding of the energy exchange within the canopy.

Can We Use Satellite-Based FAPAR to Detect Drought?

Drought in Australia has widespread impacts on agriculture and ecosystems. Satellite-based Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has great potential to monitor and assess drought impacts on vegetation greenness and health. Various FAPAR products based on satellite observations have been generated and made available to the public. However, differences remain among these datasets due to different retrieval methodologies and assumptions. The Quality Assurance for Essential Climate Variables (QA4ECV) project recently developed a quality assurance framework to provide understandable and traceable quality information for Essential Climate Variables (ECVs). The QA4ECV FAPAR is one of these ECVs. The aim of this study is to investigate the capability of QA4ECV FAPAR for drought monitoring in Australia. Through spatial and temporal comparison and correlation analysis with widely used Moderate Resolution Imaging Spectroradiometer (MODIS), Satellite Pour l’Observation de la Terre (SPOT)/PROBA-V FAPAR generated by Copernicus Global Land Service (CGLS), and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index, as well as the European Space Agency’s Climate Change Initiative (ESA CCI) soil moisture, the study shows that the QA4ECV FAPAR can support agricultural drought monitoring and assessment in Australia. The traceable and reliable uncertainties associated with the QA4ECV FAPAR provide valuable information for applications that use the QA4ECV FAPAR dataset in the future.