J. Moreno

University of Valencia, Valenza, Valencia, Spain

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Publications (132)68.59 Total impact

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    ABSTRACT: The FLuorescence EXplorer (FLEX) satellite mission, candidate of ESA's 8th Earth Explorer program, is explicitly optimized for detecting the sun-induced fluorescence emitted by plants. It will allow consistent measurements around the O2-B (687nm) and O2-A (760nm) bands, related to the red and far-red fluorescence emission peaks respectively, the photochemical reflectance index, and the structural-chemical state variables of the canopy. The sun-induced fluorescence signal, overlapped to the surface reflected radiance, can be accurately retrieved by employing the powerful spectral fitting technique. In this framework, a set of fluorescence retrieval algorithms optimized for FLEX are proposed in this study. Two main retrieval approaches were investigated: i) the optimization of the spectral fitting for retrieving fluorescence at the oxygen absorption bands; ii) the extension of the spectral fitting to a broader spectral window to retrieve the full fluorescence spectrum in the range from 670 to 780nm. The accuracy of the retrieval algorithms is assessed by employing atmosphere-surface radiative transfer simulations obtained by coupling SCOPE and MODTRAN5 codes. The simulated dataset considers more realistic conditions because it includes directional effects, and the top-of-atmosphere radiance spectra are resampled to the current specifications of the FLuORescence Imaging Spectrometer (FLORIS) planned to serve as the primary instrument aboard FLEX. The retrieval accuracy obtained at the O2-A band is strongly affected by directional effects, and better performance is found in cases where directional effects are lower. However, the best performing algorithms tested provided similar performance, the RMSE (RRMSE) is 0.044mWm−2sr−1nm−1 (6.2%) at the O2-A band, 0.018mWm−2sr−1nm−1 (2.9%) at the O2-B band, and 6.225mWm−2sr−1 (6.4%) for the spectrally integrated fluorescence emission. The promising results achieved open new perspectives extending fluorescence studies not only in limited absorption bands, but its spectral behavior in relation to different plant species, photosynthetic rates and stress occurrences.
    No preview · Article · Nov 2015
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    ABSTRACT: Most studies assessing chlorophyll fluorescence (ChlF) have examined leaf responses to environmental stress conditions using active techniques. Alternatively, passive techniques are able to measure ChlF at both leaf and canopy scales. However, the measurement principles of both techniques are different, and only a few datasets concerning the relationships between them are reported in the literature. In this study, we investigated the potential for interchanging ChlF measurements using active techniques with passive measurements at different temporal and spatial scales. The ultimate objective was to determine the limits within which active and passive techniques are comparable. The results presented in this study showed that active and passive measurements were highly correlated over the growing season across nitrogen treatments at both canopy and leaf-average scale. At the single-leaf scale, the seasonal relation between techniques was weaker, but still significant. The variability within single-leaf measurements was largely related to leaf heterogeneity associated with variations in CO2 assimilation and stomatal conductance, and less so to variations in leaf chlorophyll content, leaf size or measurement inputs (e.g. light reflected and emitted by the leaf and illumination conditions and leaf spectrum). This uncertainty was exacerbated when single-leaf analysis was limited to a particular day rather than the entire season. We concluded that daily measurements of active and passive ChlF at the single-leaf scale are not comparable. However, canopy and leaf-average active measurements can be used to better understand the daily and seasonal behaviour of passive ChlF measurements. In turn, this can be used to better estimate plant photosynthetic capacity and therefore to provide improved information for crop management.
    Full-text · Article · Oct 2015 · Journal of Experimental Botany
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    L. Alonso · J. Moreno · I. Moya · J.R. Miller

    Full-text · Dataset · Oct 2015
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    Full-text · Dataset · Sep 2015
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    ABSTRACT: Variations in photosynthesis still cause substantial uncertainties in predicting photosynthetic CO2 uptake rates and monitoring plant stress. Changes in actual photosynthesis that are not related to greenness of vegetation are difficult to measure by reflectance based optical remote sensing techniques. Several activities are underway to evaluate the sun-induced fluorescence signal on the ground and on a coarse spatial scale using space-borne imaging spectrometers. Intermediate-scale observations using airborne-based imaging spectroscopy, which are critical to bridge the existing gap between small-scale field studies and global observations, are still insufficient. Here we present the first validated maps of sun-induced fluorescence in that critical, intermediate spatial resolution, employing the novel airborne imaging spectrometer HyPlant. HyPlant has an unprecedented spectral resolution, which allows for the first time quantifying sun-induced fluorescence fluxes in physical units according to the Fraunhofer Line Depth Principle that exploits solar and atmospheric absorption bands. Maps of sun-induced fluorescence show a large spatial variability between different vegetation types, which complement classical remote sensing approaches. Different crop types largely differ in emitting fluorescence that additionally changes within the seasonal cycle and thus may be related to the seasonal activation and deactivation of the photosynthetic machinery. We argue that sun-induced fluorescence emission is related to two processes: (i) the total absorbed radiation by photosynthetically active chlorophyll and (ii) the functional status of actual photosynthesis and vegetation stress. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
    No preview · Article · Jul 2015 · Global Change Biology
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    ABSTRACT: Remote estimation of sun-induced chlorophyll fluorescence emitted by terrestrial vegetation can provide an unparalleled opportunity to track spatio-temporal variations of photosynthetic efficiency. Here we provide the first direct experimental evidence that the two peaks of the chlorophyll fluorescence spectrum can be accurately mapped from high-resolution radiance spectra and that the signal is linked to variations in actual photosynthetic efficiency. Red and far-red fluorescence measured using a novel airborne imaging spectrometer over a grass carpet treated with an herbicide known to inhibit photosynthesis was significantly higher than the corresponding signal from an equivalent untreated grass carpet. The reflectance signal of the two grass carpets was indistinguishable, confirming that the fast dynamic changes in fluorescence emission were related to variations in the functional status of actual photosynthesis induced by herbicide application. Our results from a controlled experiment at the local scale illustrate the potential for the global mapping of terrestrial photosynthesis through space-borne measurements of chlorophyll fluorescence.
    Full-text · Article · Feb 2015
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    ABSTRACT: Since conventional air pollution monitoring stations provide coarse-scale information on exposure to pollutants, only , a growing interest in monitoring and modeling urban air pollution to obtain information with a higher spatial resolution is apparent. One of the possibilities of street-scale monitoring is biomonitoring of urban vegetation. With increasing traffic intensity, leaves act as a natural sink for particulate matter (PM) (Kardel et al., 2011; Maher et al., 2008), and can even enrich in nitrogen (Laffray et al., 2010) or heavy metals, such as lead (Gajic et al., 2009). Besides deposition, retention and even enrichment of trace elements and metals, leaves are exposed to a whole range of traffic-induced gaseous pollutants such as nitrogen oxides (NOx), carbon monoxide (CO), carbon dioxide (CO2), sulfur dioxide (SO2) which have an impact on their physiological behavior. Biomonitoring of natural vegetation allows the acquisition of well-defined samples at an affordable cost and allows the determination of air pollution at different time-scales. It reflects longer-term changes of environmental quality, because plant leaves accumulate pollution over months, or even years for evergreen species. Pollutants absorbed by vegetation can also be fixed into the plant system. By phytoremediation, i.e. the use of plants to mitigate pollutant concentrations in contaminated soils, water, or air, several tree species can be used to detoxify urban air affected by a high traffic load (Kvesitadze et al., 2006). Another advantage of a biomonitoring approach is the high spatial resolution that can be obtained.
    Full-text · Technical Report · Dec 2014
  • G. Grau · J. Vicent · J. Moreno
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    ABSTRACT: Topography alters the vertical structure of the atmosphere and, therefore, its radiative properties regarding the reflection and transmission of the solar radiation. Also it modifies the conditions of illumination of terrain, with remarkable influence in the remote sensing measures of the terrestrial surface in the optical spectrum. In this work we have applied two models of atmospheric and radiometric correction on an ENVISAT/MERIS image, considering the topography, to analyse the importance of such effects. For this, we have exploited the recent rise of Digital Models of Elevation (MDE) sufficiently detailed and precise, available to a global scale, that open new prospects for the topographical corrections of remote sensing data. The results show the adjustment of the conjoint correction model (atmospheric and topographical) in the considered case, improving comparison of spectral signatures of similar surfaces independently of the elevation or the conditions of illumination, compensating the relative variations caused by the topography in the reflectivity measured by sensors. Although the remote sensing of the terrestrial surface has tended traditionally to avoid the bands of atmospheric absorption, a peculiarity that presents the ENVISAT/MERIS images is the availability of a band (O2A) of absorption of the oxygen, located in the 761.5 nm. This band is used mainly for atmospheric corrections (estimate of the surface’s pressure, elevation of clouds, aerosols effects, etc.). But also it has been employed recently to determine the fluorescence of the vegetation, consequently this band of absorption has received remarkable attention in the last years. Considering that this absorption of the oxygen is strongly affected for topography, the determination of information on the terrestrial surface from this absorption of the oxygen requires a very precise correction of the topographical effects. Therefore in this work we analyse in particular the effect of the peak of reflectivity at 761.5 nm originated by an inappropriate correction of the topography and we study the existent relationship between the local atmospheric pressure and the depth band of absorption of the oxygen in this wavelength. © 2014 Asociacion Espanola de Teledeteccion. All rights reserved.
    No preview · Article · Dec 2014 · Revista de Teledeteccion
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    Full-text · Dataset · Oct 2014
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    ABSTRACT: The FLuorescence EXplorer (FLEX), a candidate mission for ESA’s Earth Explorer 8, will be the first space mission optimized for estimation of terrestrial vegetation fluorescence at a global scale. The mission is proposed to fly in tandem with ESA’s Copernicus Sentinel-3 satellite. On board FLEX, the Fluorescence Imaging Sensor (FLORIS), will measure the radiance between 500 and 800 nm with a bandwidth between 0.1 nm and 2 nm, providing images with a 150 km swath and 300 m pixel size. This information will improve the methods for the estimation of classical biophysical parameters, as well as the introduction of fluorescence-related products, e.g., fluorescence yield. These products will allow a more thorough study of vegetation physiological status such as actual photosynthetic activity. Eventually, this information will improve our understanding of the way carbon moves between plants and the atmosphere and how it affects the carbon and water cycles. Several scientific and industrial studies have been initiated by ESA to establish scientific benchmarks for the FLEX mission. One of the scientific studies is the Photosynthesis Study that considers the potential of fluorescence for quantifying photosynthesis, vegetation health, and stress status. To this end, the study involves development of a soil-vegetation-atmosphere-transfer (SVAT) model to quantitatively link fluorescence to photosynthesis. This model will eventually facilitate fluorescence retrievals from space, e.g., through inversion against FLEX observations. The SCOPE (Soil-Canopy Observation, Photosynthesis and Energy Balance) model was selected as baseline model and has been improved and extended with leaf biochemical sub-models. To facilitate the usability of SCOPE, the model has been subsequently integrated into the GUI framework of the ARTMO (Automated Radiative Transfer Models Operator) software package, hereafter referred to as ‘A-SCOPE’. Essentially, A SCOPE allows the user to: (1) configure and run SCOPE through interfaces; (2) simulate and store a massive quantity of spectra based on a look-up table (LUT); (3) plot groups of simulated spectra or fluxes with color gradients as a function of input variables; (4) export simulated spectra and associated meta-data to a text file for further processing. Because SCOPE is fundamentally designed as an energy budget model, its large number of input variables currently makes it less suitable to be implemented into an operational processing scheme. Model simplification is required. A global sensitivity analysis (GSA) has been conducted to quantify the relative importance of each input parameter to model outputs. Considering that both surface reflectance and vegetation fluorescence emission will be FLEX key level-1 products, the GSA identified the following driving variables for these outputs: leaf area index, chlorophyll content, vegetation height, maximum carboxylation capacity, Ball-Berry stomatal conductance parameter, solar zenith angle, dry matter content, leaf water content, leaf thickness, and senescent material. Non-influential variables were: Extinction coefficient for Vcmax, leaf width, azimuth difference, and observation zenith angle. By setting the least influential variables to fixed values, the SCOPE model can be considerably simplified. The simplified model will be subsequently integrated into a FLEX End-to-end simulator that enables simulation of scenes as if generated by FLEX and development of inversion strategies.
    Full-text · Conference Paper · Sep 2014
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    J Verrelst · J P Rivera · G Camps-Valls · J Moreno
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    ABSTRACT: In all generality, retrieval methods dedicated to the quantification of terrestrial biophysical variables can be categorized into three main domains: 1) parametric regression, 2) non-parametric regression, and 3) physically-based methods. For the last few years, we have made significant advances in all these domains, including the development of software to automate these methods. It eventually led to a scientific software package ARTMO (Automated Radiative Transfer Models Operator) that embodies multiple toolboxes and a suite of leaf and canopy radiative transfer models (RTMs); http://ipl.uv.es/artmo/. The following toolboxes enable to fully exploit the three retrieval domains: Parametric methods refer to the use of regression models through spectral indices. The ‘Spectral Indices’ toolbox allows systematic calculation of all possible band combinations of a sensor according to the formulation of an established index. The prediction efficiency of each index can be automatically evaluated against in-situ data or input data coming from a RTM by using a fitting curve (e.g. linear, exponential, power). Options to add noise, to control calibration/validation partitioning and various goodness-of-fit measures to assess the performances (e.g., r2, RMSE) are provided. The best performing regression model can subsequently be applied to an imagery, which leads to instantaneous mapping of the targeted biophysical variable. Non-parametric methods refer to the use of machine learning regression algorithms (MLRA). The ‘MLRA’ toolbox encompasses a collection of linear and non-linear nonparametric regression techniques such as partial least squares (PLS), neural networks (NN), support vector regression (SVR), kernel ridge regression (KRR) and Gaussian processes regression (GPR) and others. Depending on the chosen MLRA, multi-output is possible (PLS, NN, KRR) or associated uncertainty estimates are delivered (GPR). This toolbox is designed in a similar way as the Spectral Indices toolbox; with the same type of calibration and validation options and goodness-of-fit measures provided. The best performing MLRA model can subsequently be applied to an imagery which leads to instantaneous mapping of the targeted biophysical variable(s). Physically-based methods refer to the inversion of Lookup-table (LUT)-based RTMs through cost functions. This method is considered a physically-sound and robust to retrieve biophysical variables, but regularization strategies are required to mitigate the drawback of ill-posedness. The ‘Inversion’ toolbox encompasses a collection of more than 60 cost functions, originating from three different mathematical families, being: information measures, M-estimates and minimum contrast methods. Various regularization options can be introduced in the inversion, being: adding noise, multiple solutions, and data normalizing. Simultaneous retrieval of multiple variables is possible. Additional uncertainty estimates can be provided in the form of standard deviation and residuals. The best assessed inversion strategy can subsequently be applied to an imagery, which leads to mapping of the targeted biophysical variable(s). In this work, all these methods were evaluated by using Simulated Sentinel-2 data against ground-based validation data from the ESA campaign SPARC (Barrax, Spain). Results will be presented for leaf area index (LAI) retrieval. Apart from retrieval accuracy also processing speed was analyzed. This work will close with consolidated guidelines towards powerful retrieval methods that are implementable in operational processing chains.
    Full-text · Conference Paper · Sep 2014
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    Full-text · Article · Jun 2014
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    Full-text · Dataset · May 2014
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    ABSTRACT: Spatially distributed chlorophyll content of urban vegetation provides an important indicator of a plant's health status, which might depend on the habitat quality of the specific urban environment. Recent advances in optical remote sensing led to improved methodologies to monitor vegetation properties. The hyperspectral index NAOC (Normalized Area Over reflectance Curve) is one of these new tools that can be used for mapping chlorophyll content. As part of the BIOHYPE project, we present the work done to quantify vegetation chlorophyll content over the city of Valencia (Spain) based on chlorophyll measurements of four representative tree species: the London plane tree (Platanus x. acerifolia), the Canarian date palm (Phoenix canariensis), the European nettle tree (Celtisaustralis) and the white mulberry (Morus alba). Measurements were acquired during the summer of 2011, in a field campaign in which for 320 leaf samples, chlorophyll content was measured both in the laboratory and by using a SPAD-502 chlorophyll meter. Both methods were correlated (R2> 0.86), using best fit power type functions. During the field campaign an aircraft with a CASI (Compact Airborne Spectral Imager) hyperspectral sensor onboard overflew the city obtaining imagery with a spatial resolution of ~1 m suitable to identify individual urban trees. From the CASI data the NAOC index was calculated and linked with the laboratory chlorophyll content measurements. This led to a detailed chlorophyll content map with a RMSE of 15 μg cm-2. Chlorophyll map analysis at the individual crown level suggests the applicability to identify trees with lowered chlorophyll content due to a suboptimal habitat quality.
    Full-text · Conference Paper · Apr 2014
  • N Sabater · J Vicent · L Alonso · J Verrest · J Moreno
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    ABSTRACT: A new atmospheric correction algorithm is proposed to support data analysis from the ESA's 8th Earth Explorer Fluorescence EXplorer (FLEX) candidate mission. The Fluorescence Imaging Spectrometer (FLORIS) on board FLEX covers, with a very high spectral resolution, a narrow spectral range, from 500 nm to 780 nm, ideal for vegetation fluorescence detection but insufficient for atmospheric characterization. For this reason, FLEX is planned as a tandem mission with Sentinel-3 (S3). Therefore, to perform the FLEX atmospheric correction, atmospheric parameters such as aerosol optical properties and water vapour content will be estimated from S3 data. Once the atmospheric state has been characterized, a second step deals with the retrieval of surface apparent reflectance, i.e. the surface reflectance modified by the fluorescence radiance emission. The first part of this paper is dedicated to the description of the method, summarising the main steps in the atmospheric characterization and in the succeeding surface apparent reflectance retrieval. In the second part of the paper, different databases have been simulated covering a wide range of atmospheric and surface reflectance properties to show accuracy obtained with the methodology proposed, especially over O2 absorption band spectral regions. The validation task is developed by comparing apparent reflectance retrieved from the atmospheric correction algorithm and those obtained using atmospheric parameters defined in the database creation. In addition, to demonstrate that accuracy obtained from the atmospheric correction is enough to provide a precise chlorophyll fluorescence retrieval, a first fluorescence estimation have been performed for all the cases covered by the simulated databases.
    No preview · Conference Paper · Apr 2014
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    ABSTRACT: A diierential absorption technique is used in the 940 nm to re-trieve the columnar water vapour content. Geospatial co-registration between SENTINEL-3 and FLORIS Level-1 data is necesary to be performed as rst step. In addition, spectral calibra-tion of FLORIS data and cross calibration between both products is essential before starting with the atmospheric correction process. can be provided by MODTRAN5 (or can be approximated by a straight line) can be approximated by polynomial interpolation, using selected key points over entire spectral range., "MERIS/AATSR synergy algorithms for cloud screening, aerosol retrieal, and atmospheric correction," Tech. Rep., 2009., "An integrated model of soil-canopy spectral radiances, photosynthesis, uorescence, temperature and energy balance," Biogeosciences, vol. 6, no. 12, pp. 3109–3129, 2009. -Sentinel-3 level 1 lgorithms theorethical baseline document-part 2, " Optical products[SY-24], vol. Level 1c ARBD, no. Ref.:S3-DD-TAF-SY-0062. BIBLIOGRAPHY (Eq.2) (Eq.3) (Eq.4) () -2 -1 -1 0.2 mWm sr nm s F ε ≤ Integrated values at canopy level are the ones required by models. for instantaneous observations. 300 m original spatial resolution. Includes as subproducts carotenoids / chlorophyll ratio and violaxanthin / zeaxan-thin ratio, responsible for regulated energy dissipation. Accounts for the fraction of light absorbed by non-photochemical pigments (anthocyanin). Ratio between energy emitted as uorescence versus energy absorbed by chlorophyll-a. Accounts for actual chlorophyll speciic absorption. Actual electron current after charge separation at PSII, also accounts for instantaneous surface temperature eeects. Deened as "actual photosynthesis / potential photosynthesis" Deened at Level-2, but recommended usage as Level-3 product m FLEX is planned as a tandem mission with Copernicus' mission Sen-tinel-3 (S3). S-3 instruments are necessary to extract information about the atmosphere and to perform an accurate atmospheric co-rrection of the acquired images. S3's Ocean and Land Colour Imaging spectrometer (OLCI), cove-ring from 400 nm to 1020 nm, and the Sea and Land Surface Tem-perature Radiometer (SLSTR), covering from visible to Thermal Infrared (TIR) with its dual view, will provide the information needed to characterize the atmosphere. FLEX SENTINEL-3
    No preview · Conference Paper · Mar 2014
  • N Sabater · J P Rivera · J Vicent · L Alonso · J Verrelst · J Moreno
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    ABSTRACT: A detailed description of FLEX END-TO-END Simulator (E2ES) scientific modules, i.e. the Scene Generator (SG) and the Level-2 Retrieval (L2R) modules is presented in this paper. On one hand, the SG offers the possibility to simulate a wide range of realistic scenarios for FLEX/Sentinel-3 (S3) tandem mission by coupling two radiative transfer codes, at soil level and at atmospheric level. On the other hand, the L2R contains a set of algorithms able to perform the atmospheric correction and the fluorescence retrieval only using Top Of Atmosphere (TOA) radiances as input. In addition, L2R provides as output not only fluorescence radiance, but also a list of biophysical parameters such as Chlorophyll Content (Chl.) and Leaf Area Index (LAI) among others. In the literature, many SGs for optic passive missions only offer a collection of images predefined off-line. User simulation capabilities are then restricted to choose between one of those predefined images. However, FLEX SG allows the user to define its own scene configuring atmospheric and surface properties. In addition, the L2R does not require the usage of any auxiliary input data, which makes this module autonomous.
    No preview · Conference Paper · Mar 2014
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    ABSTRACT: Passive steady-state chlorophyll fluorescence (Fs) provides a direct diagnosis of the functional status of vegetation photosynthesis. With the prospect of mapping Fs using remote sensing techniques, field measurements are mandatory to understand to which extent Fs allows detecting plant stress in different environments. Trees of four common species in Valencia were classified in either a low or a high local traffic exposure class based on their leaf magnetic value. Upward and downward hyperspectral fluorescence yield (FY) and indices based on the two Fs peaks (at 687 and 741 nm) were calculated. FY indices of P. canariensis and P. x acerifolia were significantly different between the two traffic exposure classes defined, but not for C. australis nor M. alba. While chlorophyll content could not indicate the difference between low and high traffic exposure, the FY(687)/FY(741) peak ratio increased significantly (p < 0.05) for both leaf sides for the higher traffic exposure class.
    No preview · Article · Jan 2014 · Environmental Pollution

  • No preview · Conference Paper · Jan 2014
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    ABSTRACT: FLEX (Fluorescence EXplorer) is a candidate for the 8th ESA's Earth Explorer mission. Is the first space mission specifically designed for the estimation of vegetation fluorescence on a global scale. The mission is proposed to fly in tandem with the future ESA's Sentinel-3 satellite. It is foreseen that the information obtained by Sentinel-3 will be supplemented with that provided by FLORIS (Fluorescence Imaging Spectrometer) onboard FLEX. FLORIS will measure the radiance between 500 and 800 nm with a bandwidth between 0.1 nm and 2 nm, providing images with a 150 km swath and 300 m pixel size. This information will allow a detailed monitoring of vegetation dynamics, by improving the methods for the estimation of classical biophysical parameters, and by introducing a new one: fluorescence. This paper presents the current status of FLEX mission in A/B1 phase and the different ongoing studies, campaigns and projects carried out in support of the FLEX mission.
    No preview · Article · Jan 2014 · Revista de Teledeteccion