The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring of steady-state chlorophyll fluorescence in terrestrial vegetation. Fluorescence is a sensitive probe of photosynthetic function in both healthy and physiologically perturbed vegetation, and a powerful non-invasive tool to track the status, resilience, and recovery of photochemical processes and moreover provides important information on overall photosynthetic performance with implications for related carbon sequestration. The early responsiveness of fluorescence to atmospheric, soil and plant water balance, as well as to atmospheric chemistry and human intervention in land usage makes it an obvious biological indicator in improving our understanding of Earth system dynamics. The amenability of fluorescence to remote, even space-basedobservation qualifies it to join the emerging suite of space-based technologies for Earth observation. FLEX would encompass a three-instrument array for measurement of the interrelated features of fluorescence, hyperspectral reflectance, and canopy temperature. FLEX would involve a space and ground-truthing program of 3-years duration and would provide data formats for research and applied science.

An atmospheric correction algorithm for the retrieval of land surface reflectance from the Medium Resolution Imaging Spectrometer (MERIS) data has been implemented. The algorithm is designed to obtain the main atmospheric parameters needed in the correction from the image itself, leading to an optimal characterization of the atmospheric state, in temporal and spatial resolution terms. The first part of this paper is devoted to the description of the method, outlining the main steps in the atmospheric characterization and in the subsequent surface reflectance retrieval. The validation task is detailed in the second part. Both the comparison of the algorithm performance with simulated data and with AERONET measurements show a high accuracy in the atmospheric and surface reflectance products.

ABSTRACT Algorithms have been developed to estimate vegetation biophysical variables (the products) from MERIS top of canopy reflectance observations. This includes the leaf area index (LAI), the fraction of photosynthetically active radiation absorbed by the canopy (fAPAR), the cover fraction (fCover), and the canopy integrated chlorophyll content (LAI.C ab ).. The algorithm is based on the training of neural networks over an extensive data set representing a large variability in canopy characteristics made of radiative transfer model simulations (SAIL, PROSPECT). The architecture of the back-propagation neural network was optimized for each biophysical variable and provides good theoretical performances for fAPAR and fCover, while estimates of LAI and LAI.C ab for the denser vegetation shows a degradation of the performances due to saturation. Preliminary validation of the products confirmed the theoretical performances as compared to other satellite products (MODIS, MGVI) and ground measurements.

Many vegetation properties are related to features of reflectance spectra in the region 400 nm - 2500 nm. and to emittance in region 8 mm - 14 mm Detailed observations of spectral reflectance reveal subtle features related to biochemical components of leaves such as chlorophyll and water. Exchange of energy between the biosphere and the atmosphere is an important mechanism determining the response of vegetation to climate variability. This requires measurements of the component temperature of foliage and soil. The latter are closely related to the angular variation in thermal infrared emittance. The architecture of vegetation canopies determines complex changes of observed reflectance and emittance spectra with view and illumination angle. Quantitative analysis of reflectance and emittance spectra requires, therefore, an accurate characterization of the anisotropy of radiance. This can be achieved with nearly - simultaneous observations at different view angles. The Surface Processes and Ecosystem Changes Through Response Analysis (SPECTRA) Mission has been conceived to perform these observations at high spatial resolution by taking advantage of the spacecraft agility. Scientific preparations are pursued along two avenues: a) the nature of the expected data and candidate algorithms are evaluated by generating and using synthetic hyper - spectral multi - angular/radiometric data; b) algorithms are evaluated with actual hyper - spectral data collected with a variety of airborne systems and concurrent ground measurements; Campaigns have been performed using radiometric observations provided by ATSR, AATSR, AirMISR, CHRIS - PROBA and a variety of airborne hyperspectral systems. The paper will cover highlights of these studies.

SPECTRA (Surface Processes and Ecosystem Changes through Response Analysis) is a planned spaceborne multiangular hyperspectral and thermal imaging spectrometer in phase A early design led by ESA's earth observation group. Its mission is to describe, understand and model the role of terrestrial vegetation in the global carbon cycle and its response to climate variability. Even though the project has been terminated in November 2005, many results of the phase A studies are considered to be useful as input to future missions. The SPECTRA end-to-end simulator is intended to be used to test different aspects of the SPECTRA mission concept and for tuning the retrieval algorithms as well as assessing their performances. The intention of this ESA-commissioned study was not to build an actually working simulator, but to conceive an architecture for a simulator to be built during phase B of the SPECTRA design, as well as perform a limited validation of this architecture. The software architecture for the future SPECTRA end-to-end simulator has been designed to be modular, flexible and distributed. It consists of a central control unit with associated database, which is controlled and monitored via an internet-accessible web interface, and a flexible number of modules performing the actual calculations. The list of simulator modules currently includes but is not limited to state-of-the-art developments in radiative transfer (Onera), instrument modelling (ESA), atmospheric correction (Onera), and various level 2 algorithms (Alterra). Assimilation models and global carbon flux models are linked to the simulator via the SPECTRA field segment database (RSL and Princeton), for which a high level schema has been defined. The simulator structure has been validated using full end-to-end simulations from ground data to top-of-atmosphere, through the SPECTRA instrument simulator provided by industry, and back again. Test data from the Barrax field site are used for this purpose (University of Valencia).