1. Contact © European Union, 2012 https://ec.europa.eu/jrc Monitoring the State of the Global Terrestrial Surfaces The state of vegetation is analysed using estimates of FAPAR from 1998-2014 using SeaWiFS, MERIS and JRC MODIS-TIP products (Retrieval algorithms are summarized on the top right panel). These latter algorithms are used to provide the two QA4ECV FAPAR products. JRC FAPAR will be designed for using long time series of AVHRR surface reflectances and TIP will assimilate QA4ECV albedo products. Temporal and global anomalies derived from the analysis of this time series highlight geographical regions subject to changes in 2014 with respect to previous years. JRC Two-Stream Inversion Package BRF TOA BRF TOC FAPAR Rectified Red Angular/Atmospheric effects Angular/Atmospheric effects Rectified NIR Optimization Procedure Optimization Procedure Building Global Monthly Times Series The 0.5°x0.5° monthly products derived from MODIS TIP and MERIS have been compared at global scale and a correction of bias, corresponding to the average of differences over common years, i.e. 2004-2011, have been applied on each grid cell. These values vary with both space and times (Gobron & Robustelli, 2013) The mean globally averaged anomalies, smoothed using a six-month running average, indicate that year 2014 corresponds to relatively healthy state of vegetation at global scale over the South hemisphere (red line) as was the case, for example, in 2011. = 0.0474 σ = 0.0634 Med = - 0.0017 = -0.0013 σ = 0.0343 Med = - 0.0006 Comparison before and after the correction ESA-JRC FAPAR Algorithm Description of JRC FAPAR algorithms Examples of correction values applied for January, April, July and October. JRC/ESA FAPAR products are derived from a generic RT algorithm (Gobron et. al., 1999, 2000, 2010) that uses TOA reflectance values which are decontaminated from angular, soil and atmospheric effects and estimates the instantaneous FAPAR value. JRC Two-stream Inversion Package (TIP) is based on a data assimilation technique in visible and near-infrared broadband surface albedo for retrieving state variables and then reconstructs the absorbed fluxes (Pinty et al., 2006, 2007). Temporal and global results Global anomalies highlight geographical regions subject to changes in 2014 with respect to previous years (Gobron, 2015). Time series of averaged global anomaly The left (right) panel shows the scatter-plot (histogram of difference), respectively. We can see that the bias correction reduces the averaged difference from 0.0474 to 0.0343 and the standard deviation σ from 0.0634 to 0.0343. Note that a land mask has been also applied for removing remaining MODIS albedo values over water pixels. Scatter-plots and histograms of differences between FAPAR derived from MERIS and TIP MODIS before and after the correction are illustrated below: Nadine Gobron European Commission Joint Research Centre Institute of Environment and Sustainability Land Resource Management Unit Email: nadine.gobron@jrc.ec.europa.eu