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Due to emerging high spectral resolution, remote sensing techniques and ongoing developments to retrieve the spectrally resolved vegetation fluorescence spectrum from several scales, the light reactions of photosynthesis are receiving a boost of attention for the monitoring of the Earth's carbon balance. Sensor-retrieved vegetation fluorescence (from leaf, tower, airborne or satellite scale) originating from the excited antenna chlorophyll a molecule has become a new quantitative biophysical vegetation parameter retrievable from space using global imaging techniques. However, to retrieve the actual quantum efficiencies, and hence a true photosynthetic status of the observed vegetation, all signal distortions must be accounted for, and a high-precision true vegetation reflectance must be resolved. ESA's upcoming Fluorescence Explorer aims to deliver such novel products thanks to technological and instrumental advances, and by sophisticated approaches that will enable a deeper understanding of the mechanics of energy transfer underlying the photosynthetic process in plant canopies and ecosystems.

Freshwater quality maintenance is essential for human use and ecological functions. To ensure this objective, governments establish programs for a continuous monitoring of the inland waters state. This could be possible with Sentinel-2 (S2) and Sentinel-3 (S3), two remote sensing satellites of the European Space Agency, equipped with spectral optical sensors. To determine optimal water quality algorithms applicable to their spectral bands, 36 algorithms were tested for different key variables (chlorophyll a (Chl_a), colored dissolved organic matter (CDOM), colored dissolved organic matter (TSS), phycocyanin (PC) and Secchi disk depth (SDD)). A database of 296 water-leaving reflectance spectra were used, as well as concomitant water quality measurements of Mediterranean reservoirs and lakes of Spain. Two equal data sets were used for calibration and validation. The best algorithms were recalculated using all database and used the following band relations: SDD, R560/R700, CDOM, R665/R490, PC, R705/R665 for S2 and R620, R665, R709 and R779 for S3, using a semi-analytical algorithm, R700 for TSS &lt, 20 mg/L and R783/R492 (S2) or R779/R510 (S3) for TSS &gt, 20 mg/L, and for Chl_a, the maximum (R443, R492)/R560 for Chl_a &lt, 5 mg/m3 and R700/R665 for Chl_a &gt, 5 mg/m3. A preliminary test with a satellite image in a well-known reservoir showed results consistent with the expected ranges and spatial patterns of the variables.

During the design phase of a satellite mission, end-to-end mission performance simulator (E2ES) tools allow scientists and engineers evaluating the mission concept, consolidating system technical requirements and analyzing the suitability of the implemented technical solutions and data processing algorithms. The generation of synthetic scenes is one of the core parts of an E2ES, providing scenes (ground truth) as would be observed by satellite instruments and used as reference against simulated retrieved mission products. An appropriate generation of the scene also allows assessing the performance of the ground data processing chain replacing real instrument data before the mission is in orbit, for which the fidelity of the scene generation is critical. This paper describes the design of a generic scene generator (GSG) with capabilities to generate complex 3-D synthetic scenes that combine the effects of surface, heterogeneity, topography and atmosphere, and viewing/illumination geometry. The proposed design allows generating consistent high spatial and spectral resolution top-of-atmosphere radiance scenes for multiple instruments based on the use of thematic maps, radiative transfer models, and reflectance databases. The described GSG was implemented within the FLuorescence EXplorer (FLEX) E2ES software tool and showed its capabilities to generate compatible scenes for the fluorescence imaging spectrometer, ocean and land color instrument, and sea and land surface temperature radiometer instruments of ESA’s FLEX/Sentinel-3 tandem mission and to validate the fulfillment of the FLEX mission requirements.

The atmospheric contribution constitutes about 90 percent of the signal measured by satellite sensors over oceanic and inland waters. Over open ocean waters, the atmospheric contribution is relatively easy to correct as it can be assumed that water-leaving radiance in the near-infrared (NIR) is equal to zero and it can be performed by applying a relatively simple dark-pixel-correction-based type of algorithm. Over inland and coastal waters, this assumption cannot be made since the water-leaving radiance in the NIR is greater than zero due to the presence of water components like sediments and dissolved organic particles. The aim of this study is to determine the most appropriate atmospheric correction processor to be applied on Sentinel-2 MultiSpectral Imagery over several types of inland waters. Retrievals obtained from different atmospheric correction processors (i.e., Atmospheric correction for OLI ‘lite’ (ACOLITE), Case 2 Regional Coast Colour (here called C2RCC), Case 2 Regional Coast Colour for Complex waters (here called C2RCCCX), Image correction for atmospheric effects (iCOR), Polynomial-based algorithm applied to MERIS (Polymer) and Sen2Cor or Sentinel 2 Correction) are compared against in situ reflectance measured in lakes and reservoirs in the Valencia region (Spain). Polymer and C2RCC are the processors that give back the best statistics, with coefficients of determination higher than 0.83 and mean average errors less than 0.01. An evaluation of the performance based on water types and single bands−classification based on ranges of in situ chlorophyll-a concentration and Secchi disk depth values- showed that performance of these set of processors is better for relatively complex waters. ACOLITE, iCOR and Sen2Cor had a better performance when applied to meso- and hyper-eutrophic waters, compare with oligotrophic. However, other considerations should also be taken into account, like the elevation of the lakes above sea level, their distance from the sea and their morphology.

Sun induced chlorophyll fluorescence (SICF) emitted by phytoplankton provides considerable insights into the vital role of the carbon productivity of the earth’s aquatic ecosystems. However, the SICF signal leaving a water body is highly affected by the high spectral variability of its optically active constituents. To disentangle the SICF emission from the water-leaving radiance, a new high spectral resolution retrieval algorithm is presented, which significantly improves the fluorescence line height (FLH) method commonly used so far. The proposed algorithm retrieves the reflectance without SICF contribution by the extrapolation of the reflectance from the adjacent regions. Then, the SICF emission curve is obtained as the difference of the reflectance with SICF, the one actually obtained by any remote sensor (apparent reflectance), and the reflectance without SICF, the one estimated by the algorithm (true reflectance). The algorithm first normalizes the reflectance spectrum at 780 nm, following the similarity index approximation, to minimize the variability due to other optically active constituents different from chlorophyll. Then, the true reflectance is estimated empirically from the normalized reflectance at three wavelengths using a machine learning regression algorithm (MLRA) and a cubic spline fitting adjustment. Two large reflectance databases, representing a wide range of coastal and ocean water components and scattering conditions, were independently simulated with the radiative transfer model HydroLight and used for training and validation of the MLRA fitting strategy. The best results for the high spectral resolution SICF retrieval were obtained using support vector regression, with relative errors lower than 2% for the SICF peak value in 81% of the samples. This represents a significant improvement with respect to the classic FLH algorithm, applied for OLCI bands, for which the relative errors were higher than 40% in 59% of the samples.

The FLuorescence EXplorer (FLEX) mission, selected as the European Space Agency's eighth Earth Explorer, aims to globally measure the sun-induced-chlorophyll-fluorescence spectral emission from terrestrial vegetation. In the frame of the FLEX mission, several industrial and scientific studies have analyzed the instrument design, image processing algorithms, or modeling aspects. At the same time, a common tool is needed to address the overall FLEX mission performance by combining all these features. For this reason, an end-to-end mission performance simulator has been developed for the FLEX mission (FLEX-E). This paper describes the FLEX-E software design, which combines the generation of complex synthetic scenes with an advanced modeling of the instrument behavior and the full processing scheme up to the final fluorescence product. The results derived from FLEX-E simulations indicate that the instrument and developed image processing algorithms are able to retrieve the sun-induced fluorescence with an accuracy below the 0.2 $\text{mW}\cdot\text{m}^{-2}\cdot\text{sr}^{-1}\cdot \text{nm}^{-1}$ mission requirement. It is expected that FLEX-E will not only optimize the FLEX retrieval algorithms and technical requirements, but also serve as the baseline for the ground processing implementation and testing of calibration/validation procedures.

The Ocean Color 2 (OC2), Ocean Color 3 (OC3) and Dall'Olmo three-band (TBDO) algorithms used for the estimation of the chlorophyll-a concentration [Chl-a] have been calibrated and validated for Sentinel-2 spectral bands. Measurements of in situ chlorophyll-a, radiometry and simulations with HydroLight have been used for this purpose within the Ecological Status of AQuatic Systems Satellites (ESAQS) Project to estimate water quality in aquatic systems in Spain. The results show that Sentinel-2 spectral bands are suitable for studying the chlorophyll-a concentration in inland waters. The TBDO algorithm have been applied to Sentinel-2 images and satisfactory results have been obtained in Albufera of Valencia region (Spain).

An End-to-end simulator (E2ES) is a tool to evaluate the performance of a satellite mission. Once a mission is approved for operation, E2ES evolves during Phase C/D to become a supporting tool for the development and validation of the ground data processor, as well as for simulating data sets to test the Prototype and Operational Processors. FLEX-E is the E2ES of the FLEX/Sentinel-3 tandem mission, which was selected in 2015 as ESA's eighth Earth Explorer. The FLEX-E evolution implies the consolidation of all the retrieval algorithms (e.g. fluorescence, reflectance, biophysical variables), the implementation of new scientific developments, as well the improvement of the co-registration process, the atmospheric correction, and the retrieval of the Level-2 products. The high-level modular design of the improved Level-2 retrieval module will permit a detailed analysis of the errors propagating through the processing chain.

Chlorophyll-a concentration ([Chl-a]) and Lake Surface Temperature (LST) were retrieved in Lake Titicaca (Peru-Bolivia) using MODIS and Landsat-8 images. The lake was chosen as a case-study for evaluating the feasibility of Landsat-8 images for [Chl-a] and LST monitoring in oligotrophic and mesotrophic water bodies. The big size of the lake and its spatial and temporal variability, allowed the comparison of MODIS and Landsat-8 products for a wide range of [Chl-a] and LST. The atmospheric correction of the images was facilitated by the very high altitude of the lake. MODIS images were processed with standard ocean color algorithms whereas for Landsat-8, specific algorithms were tested and validated The results show that Landsat-8 is capable of retrieving [Chl-a] and LST with an accuracy comparable to that of MODIS and with a finer spatial resolution, revealing surface patterns in greater detail. The combined use of both sensors allows monitoring the eutrophication and temperature trends of Lake Titicaca, which is a water body of the highest ecological interest, increasingly affected by human activities in its watershed and very sensitive to climate changes.

The Hyperspectral Imager for the Coastal Ocean (HICO) is an imaging spectrometer designed with a very high signal-to-noise ratio to monitor coastal ocean and inland waters. The processing of Top-Of-Atmosphere radiance data down to surface reflectance is fundamental for the retrieval of water quality products. However, the current HICO processing chain does not provide atmospheric corrected data nor higher-level water quality products. This paper describes the algorithms implemented within an HICO data processing chain that includes image pre-processing, atmospheric correction and the retrieval of water quality parameters. The implemented algorithms have been validated over a set of HICO images showing a good match with in-situ surface reflectance data and correlation (R2 = 0.95) between in-situ measured and retrieved Chl-a over a water body. It is expected that the presented algorithms will ease the processing of HICO data down to surface reflectance allowing to derive water quality parameters.

[EN] Chlorophyll-a concentration is one of the main indicators of inland waters quality. Using CHRIS/PROBA images and in situ data obtained in four lakes in Colombia and Spain, we obtained empirical models for the estimation of chlorophyll-a concentration, which can be directly applied to future images of MSI Sentinel-2 and OLCI Sentinel-3 sensors. The models, based on spectral band indices, were validated with data from the hyperspectral sensor HICO, onboard of the International Space Station., [ES] La concentración de clorofila-a es uno de los principales indicadores de la calidad de las aguas continentales. A partir de imágenes del sensor CHRIS/PROBA y de datos obtenidos en campañas de medida en lagos en Colombia y España, se han obtenido modelos empíricos para la estimación de la concentración de clorofila-a, directamente aplicables a los futuros sensores de la ESA, MSI de Sentinel-2 y OLCI de Sentinel-3. Los modelos, basados en índices de bandas espectrales, se han validado con datos del sensor hiperespectral HICO, a bordo de la Estación Espacial Internacional., Se agradece al CEDEX por facilitarnos los datos de radiometría in situ y de [Chl-a] del Embalse de Rosarito y La Albufera, y al Grupo de Ecología de la Universidad de Valencia por los datos de [Chl-a] medidos en la Albufera.

The simulation of synthetic images serve scientists and engineers to study the instrument configuration as well as to develop image processing and retrieval strategies for a sensor in development. Despite synthetic scene simulators have been developed in the past in the frame of satellite missions, their functionality and flexibility to create a user-defined scene is limited by their architecture, design and implementation. This paper introduces the design of a generic scene simulator with the flexibility to generate realistic synthetic scenes by configuration of the surface and atmosphere. Following this generic design, a scene simulator is being developed for the ESA's Earth Explorer 8th candidate mission FLEX in order to reproduce the high spectral resolution signal acquired by its hyperspectral instrument. The proposed design and architecture can be adapted to any other passive optical space and airborne instruments.

The Hyperspectral Imager for the Coastal Ocean (HICO) is an imaging spectrometer specifically designed to monitor the coastal ocean. The processing of Top-Of-Atmosphere (TOA) radiance data down to surface reflectance is fundamental for the retrieval of water quality products. However, the current HICO processing chain does not provide atmospheric corrected data nor higher-level water quality products. This work describes a toolbox for the atmospheric correction of HICO data and the retrieval of water quality products. The HICO toolbox, consisting on three main modules (image pre-processing, atmospheric correction and retrieval of water quality products), has been used over a set of HICO images showing a good linear correlation (R2 = 0.95) between in-situ measured and retrieved Chl-a over a water body. The presented toolbox will ease the processing of HICO data down to surface reflectance that will allow to derive water quality parameters.

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. In this paper 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 (Celtis australis)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 (R-2 > 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 similar to 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 mu g 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. (C) 2014 Elsevier Ltd. All rights reserved.

[EN] 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., [ES] La misión FLEX (FLuorescence EXplorer) candidata del programa “Earth Explorer” de la ESA, es la primera misión espacial diseñada específicamente para la estimación de la fluorescencia de la vegetación a escala global. La propuesta incluye que FLEX vuele en tándem con el futuro Sentinel-3 de la ESA. La información proporcionada por los sensores de Sentinel-3 será complementada con la proporcionada por FLORIS (FLuORescence Imaging Spectrometer) a bordo de FLEX, que medirá la radiancia entre 500 y 800 nm con una anchura de bandas entre 0,1 nm y 2 nm, proporcionando imágenes con un ancho de barrido de 150 km y tamaño de pixel de 300 m. Esta información permitirá el estudio detallado de la vegetación con métodos mejorados para la estimación de parámetros biofísicos clásicos y la introducción de nuevos parámetros biofísicos como la fluorescencia. En este trabajo se muestra el estado actual de la misión FLEX en fase A/B1 y de los distintos estudios, campañas y proyectos que se están llevando a cabo en torno a la misión FLEX., Este trabajo ha sido posible gracias al Proyecto AYA2010-21432-C02-01 (BIOFLEX) subvencionado por el Ministerio de Economía y Competitividad de España.