Envisat's Medium Resolution Imaging Spectrometer (MERIS) Algorithm Theoretical Basis Document: FAPAR and Rectied Channels over Terrestrial Surfaces

This Algorithm Theoretical Basis document (ATBd) describes the Joint Research Center (JRC) procedure used to retrieve information of absorbed photosynthetical radiation by the vegetated terrestrial surfaces from an analysis of the Top Of Atmosphere (TOA) data acquired by MERIS. The code of the proposed algorithm takes the form of a set of several formulae which transform calibrated spectral directional reflectances into a single numerical value. These formulae are designed to extract the green Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) in the plant canopy from the measurements and the rectified channels in the red and near-infrared bands. The methodology described in this document has been optimized to assess the presence on the ground of healthy live green vegetation. The main optimization procedure has been constrained to provide an estimate of FAPAR in the plant canopy, although the outputs are expected to be used in a wide range of applications. This algorithm delivers, in addition to the FAPAR product, the so-called rectified reflectance values in the red and near-infrared spectral bands. These are virtual reflectances largely decontaminated from atmospheric and angular effects. It also provides a categorization of pixel types thanks to a pre-processing identification based on multi-spectral properties. These two virtual reflectances are also computed over bare soils using specific coefficients. This document identifies the sources of input data, outlines the physical principles and mathematical background justifying this approach, describes the proposed algorithm, and lists the assumptions and limitations of this technique.JRC.DDG.H.3-Global environement monitorin

Landsat 7 Enhanced Thematic Mapper JRC-FAPAR Algorithm Theoretical Basis Document

This Algorithm Theoretical Basis document (ATBd) describes the Joint Research Center (JRC)- procedure used to retrieve information of absorbed photosynthetical radiation by the vegetated terrestrial surfaces from an analysis of the Top Of Atmosphere (TOA) data acquired by the Landsat 7 Enhanced Thematic Mapper (ETM+) instrument. The corresponding data consist of eight spectral bands, with a spatial resolution of 30 meters for bands 1 to 5 and band 7 whereas the resolution for band 6 (thermal infrared) is 60 meters and resolution for band 8 (panchromatic) is 15 meters. Approximate scene size is 170 km north-south by 183 km east-west. The code of the proposed algorithm takes the form of a set of several formulae which transform calibrated spectral directional reflectances into a single numerical value. These formulae are designed to extract the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) in the plant canopy from the measurements. The methodology described in this document has been optimized to assess the presence on the ground of healthy live green vegetation. The optimization procedure has been constrained to provide an estimate of FAPAR in the plant canopy, although the outputs are expected to be used in a wide range of applications. This algorithm delivers, in addition to the FAPAR product, the so-called rectied reflectance values in the red and near-infrared spectral bands (Landsat 7 ETM+ Band 3 and Band 4). These are virtual reflectances largely decontaminated from atmospheric and angular effects. It also provides a categorization of pixel types thanks to a pre-processing identication based on multi-spectral properties.JRC.H.3-Global environement monitorin

Land Surface Indicators from Space: Methodology and Preliminary Results

This document overviews the content and the preliminary results of a specific work package entitled Land Surface Indicators from Space of the Land Use and Landscapes from the Joint Research Center (JRC) and the European Environment Agency (EEA) 2006 work plan described in Kennedy and Stanners (2005). The first section summarizes the objectives of the activities in the context of the EEA project Land and Ecosystems Accounts. The main goal is the estimate and the analysis of the Net Primary Productivity (NPP) over terrestrial surfaces from space remote sensing products over various land cover types in Europe. The Knorr and Heimann (1995)'s model is applied to compute the NPP using the current JRC- Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) products as input. This simple generic global biosphere model requires also the downward photosynthetic active radiation (PAR) at the surface level. Sections 3, 4 and 5 outline the model, identify the sources of input data stream, and present preliminary results over European countries, respectively. Concluding remarks and perspectives are then given at the end of the document.JRC.H.3-Global environement monitorin

Harmonization of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from Sea-Viewing Wide Field-of-View Sensor SeaWiFS) and Medium Resolution Imaging Spectrometer Instrument (MERIS)

This paper describes the combination of terrestrial vegetation observations from two sensors, providing a historical dataset used for an in-depth analysis of the corresponding spatio-temporal patterns. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is an important variable suitable for regional to large-scale monitoring of climate impacts on vegetation. In this work, we create an extensive dataset of FAPAR using a 10-day product at $\sim$1 km resolution from September, 1997, to April, 2012, combining information from two sensors: the NASA/Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the European Space Agency (ESA)/Medium Resolution Imaging Spectrometer Instrument (MERIS). The proposed methodology reduces the noise, fills the gaps and corrects for the spurious trends in the data, providing a time-consistent coverage of FAPAR. We develop a fast merging method and evaluate its performance over Europe and the Horn of Africa.JRC.H.7-Climate Risk Managemen

On The Response Of The European Vegetation Phenology To Hydroclimatic Anomalies

Climate change is expected to alter vegetation and carbon cycle processes, with implications for ecosystems and feedback to regional and global climate. Notably, understanding the sensitivity of vegetation to the anomalies of precipitation and temperature over different land cover classes and the corresponding temporal response is essential for improved climate prediction. In this paper, we analyse vegetation response to hydroclimatic forcings using the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) derived from SeaWiFS (1998-2002) and MERIS (2003-2011) sensors at 1 km resolution. Based on land cover and pixel-wise analysis, we quantify the extent of the dependence between the FAPAR, and ultimately the phenology, and the anomalies of precipitation and temperature over Europe. Statistical tests are performed to establish where this correlation may be regarded as statistically dependent. Further, we assess a statistical link between the climate variables and a set of phenological metrics defined from FAPAR measurement. Variation in the phenological response to the unusual values of precipitation and temperature can be interpreted as the result of balanced opposite effects of water and temperature on vegetation processes. Results suggest very different responses on different land cover classes and timing seasons. The degree of observed coupled behaviour also indicates that European phenology may be quite sensitive to the perturbations in precipitation and temperature regimes such as those induced by the climate change.JRC.H.7-Climate Risk Managemen

Comparing the effectiveness of recent algorithms to fill and smooth incomplete and noisy time series

Geophysical time series often feature missing data or data acquired at irregular times. Procedures are needed to either resample these series at systematic time intervals or to generate reasonable estimates at specified times in order to meet specific user requirements or to facilitate subsequent analyses. Interpolation methods have long been used to address this problem, taking into account the fact that available measurements also include errors of measurement or uncertainties. This paper inspects some of the currently used approaches to fill gaps and smooth time series (smoothing splines, Singular Spectrum Analysis and Lomb-Scargle) by comparing their performance in either reconstructing the original record or in minimizing the Mean Absolute Error (MAE) between the underlying model and the available data, using both artificially-generated series or well-known publicly available records. Some methods make no assumption on the type of variability in the data while others hypothesize the presence of at least some dominant frequencies. It will be seen that each method exhibits advantages and drawbacks, and that the choice of an approach largely depends on the properties of the underlying time series and the objective of the research.JRC.H.5-Land Resources Managemen

MERIS Level 3 Land Surface Aggregated Products Description

This document describes the format of the products of the Medium Resolution Imaging Spectrometer (MERIS) Level 3 aggregated products. These data are operationally processed and produced at the Grid Processing-on-Demand (G-POD) of European Space Research INstitute (ESRIN) using the European Commission – DG Joint Research Centre (JRC) algorithm and software.JRC.H.3-Global environement monitorin

Technical Note: Comparing the effectiveness of recent algorithms to fill and smooth incomplete and noisy time series

Geophysical time series often feature missing data or data acquired at irregular times. Procedures are needed to either resample these series at systematic time intervals or to generate reasonable estimates at specified times in order to meet specific user requirements or to facilitate subsequent analyses. Interpolation methods have long been used to address this problem, taking into account the fact that available measurements also include errors of measurement or uncertainties. This paper inspects some of the currently used approaches to fill gaps and smooth time series (smoothing splines, Singular Spectrum Analysis and Lomb-Scargle) by comparing their performance in either reconstructing the original record or in minimizing the Mean Absolute Error (MAE), Mean Bias Error (MBE), chi-squared test statistics and autocorrelation of residuals between the underlying model and the available data, using both artificially-generated series or well-known publicly available records. Some methods make no assumption on the type of variability in the data while others hypothesize the presence of at least some dominant frequencies. It will be seen that each method exhibits advantages and drawbacks, and that the choice of an approach largely depends on the properties of the underlying time series and the objective of the research

Index for the EU global climate change alliance plus flagship Initiative

This report proposes an index to allow an ex-ante evaluation of the structural features of vulnerability to climate change for the countries identified by the Global Climate Change Alliance plus Flagship Initiative (GCCA+). It is clear from the overarching goals of the GCCA+ programme, that to rank the countries according to eligibility for funding the following issues need to be considered: vulnerability to climate change, adaptive capacity, climate change mitigation action, disaster risk, and a (political) commitment to respond to climate change and poverty reduction. The GCCA+ index identifies those countries most vulnerable to climate change and ranks them according to their eligibility for funding within the context of the EU GCCA+ programme classifying 34 “fit for purpose indicators” along one of four components (natural hazards, exposure, vulnerability and capacity). The list 34 ‘fit-for-purpose’ indicators has been compiled on the basis of their relevance with the GCCA+ programme, and the compliance with the following criteria: reliable, open source, consistent, scientifically robust, with global coverage, and based on data which are in the public domain. The indicators cover the social, economic and environmental aspects of each of the components under which they have been classified. Each indicator is described in terms of relevance, measuring unit, indicator creation method, data source, periodicity, missing data and geographical distribution in the sample of countries for the latest available year. The methodology applied to calculate the GCCA+index adopts a climate resilient development approach integrating the development policy perspective with a climate change risk management approach. The index is applied to five different samples of countries. The results of ranking the countries by the GCCA+ Index are shown in maps and tables.JRC.H.7-Climate Risk Managemen