Jorge Vicent

Universitat de València

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Neus Sabater

Finnish Meteorological Institute

Jochem Verrelst

Parc Científic de la Universitat de València

J. Moreno

Parc Científic de la Universitat de València

Luis Alonso

Fundación General

Juan Pablo Rivera

Universidad Autónoma de Nayarit

Gustau Camps‐Valls

Universitat de València

Luca Martino

Universidad Rey Juan Carlos

Carolina Tenjo

Parc Científic de la Universitat de València

Jordi Muñoz-Marı́

Parc Científic de la Universitat de València

Sergio Cogliati

University of Milano-Bicocca

Cooperative Institutions

Universitat de València

Parc Científic de la Universitat de València

Universidad de Cádiz

European Space Research and Technology Centre

Instituto de Ciencias Marinas de Andalucía

University of Milan

Goddard Space Flight Center

Wageningen University & Research

Consejo Superior de Investigaciones Científicas

University of Milano-Bicocca

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Invertible Neural Networks for Probabilistic Aerosol Optical Depth Retrieval

IEEE Transactions on Geoscience and Remote Sensing (2025)

Paolo Pelucchi Jorge Vicent Philip Stier Gustau Camps‐Valls

10.1109/tgrs.2025.3540173

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Citations (0)

Automatic emulator and optimized look-up table generation for radiative transfer models

Luca Martino Jorge Vicent Gustau Camps‐Valls

This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an optimal look-up-table for atmospheric correction based on MODTRAN5.

Interpolation

Table (database)

Flatness (cosmology)

10.1109/igarss.2017.8127241

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Citations (19)

Gaussian Process Regression Hybrid Models for the Top-of-Atmosphere Retrieval of Vegetation Traits Applied to PRISMA and EnMAP Imagery

Remote Sensing (2024)

Ana B. Pascual-Venteo Jose L. Garcia Katja Berger José Estévez Jorge Vicent

The continuous monitoring of the terrestrial Earth system by a growing number of optical satellite missions provides valuable insights into vegetation and cropland characteristics. Satellite missions typically provide different levels of data, such as level 1 top-of-atmosphere (TOA) radiance and level 2 bottom-of-atmosphere (BOA) reflectance products. Exploiting TOA radiance data directly offers the advantage of bypassing the complex atmospheric correction step, where errors can propagate and compromise the subsequent retrieval process. Therefore, the objective of our study was to develop models capable of retrieving vegetation traits directly from TOA radiance data from imaging spectroscopy satellite missions. To achieve this, we constructed hybrid models based on radiative transfer model (RTM) simulated data, thereby employing the vegetation SCOPE RTM coupled with the atmosphere LibRadtran RTM in conjunction with Gaussian process regression (GPR). The retrieval evaluation focused on vegetation canopy traits, including the leaf area index (LAI), canopy chlorophyll content (CCC), canopy water content (CWC), the fraction of absorbed photosynthetically active radiation (FAPAR), and the fraction of vegetation cover (FVC). Employing band settings from the upcoming Copernicus Hyperspectral Imaging Mission (CHIME), two types of hybrid GPR models were assessed: (1) one trained at level 1 (L1) using TOA radiance data and (2) one trained at level 2 (L2) using BOA reflectance data. Both the TOA- and BOA-based GPR models were validated against in situ data with corresponding hyperspectral data obtained from field campaigns. The TOA-based hybrid GPR models revealed a range of performance from moderate to optimal results, thus reaching R2 = 0.92 (LAI), R2 = 0.72 (CCC) and 0.68 (CWC), R2 = 0.94 (FAPAR), and R2 = 0.95 (FVC). To demonstrate the models’ applicability, the TOA- and BOA-based GPR models were subsequently applied to imagery from the scientific precursor missions PRISMA and EnMAP. The resulting trait maps showed sufficient consistency between the TOA- and BOA-based models, with relative errors between 4% and 16% (R2 between 0.68 and 0.97). Altogether, these findings illuminate the path for the development and enhancement of machine learning hybrid models for the estimation of vegetation traits directly tailored at the TOA level.

10.3390/rs16071211

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Citations (2)

Response to Referee #2

Jorge Vicent

10.5194/gmd-2019-188-ac3

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Citations (0)

Retrieval of sun induced fluorescence using advanced spectral fitting methods from radiative transfer simulations and from HyPlant imagery

Sergio Cogliati Jorge Vicent J. Moreno Tommaso Julitta Francisco Pinto

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Citations (1)

Design of a satellite end-to-end mission performance simulator for imaging spectrometers and its application to the ESA's FLEX/Sentinel-3 tandem mission

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2015)

Jorge Vicent Neus Sabater Carolina Tenjo J. R. Acarreta María Manzano

The performance analysis of a satellite mission requires specific tools that can simulate the behavior of the platform; its payload; and the acquisition of scientific data from synthetic scenes. These software tools, called End-to-End Mission Performance Simulators (E2ES), are promoted by the European Space Agency (ESA) with the goal of consolidating the instrument and mission requirements as well as optimizing the implemented data processing algorithms. Nevertheless, most developed E2ES are designed for a specific satellite mission and can hardly be adapted to other satellite missions. In the frame of ESA's FLEX mission activities, an E2ES is being developed based on a generic architecture for passive optical missions. FLEX E2ES implements a state-of-the-art synthetic scene generator that is coupled with dedicated algorithms that model the platform and instrument characteristics. This work will describe the flexibility of the FLEX E2ES to simulate complex synthetic scenes with a variety of land cover classes, topography and cloud cover that are observed separately by each instrument (FLORIS, OLCI and SLSTR). The implemented algorithms allows modelling the sensor behavior, i.e. the spectral/spatial resampling of the input scene; the geometry of acquisition; the sensor noises and non-uniformity effects (e.g. stray-light, spectral smile and radiometric noise); and the full retrieval scheme up to Level-2 products. It is expected that the design methodology implemented in FLEX E2ES can be used as baseline for other imaging spectrometer missions and will be further expanded towards a generic E2ES software tool.

FLEX

Payload (computing)

Imaging spectrometer

Earth observation

10.1117/12.2189889

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A sun-induced vegetation fluorescence retrieval method from top of atmosphere radiance for the FLEX/Sentinel-3 TanDEM mission

Neus Sabater Luis Alonso Sergio Cogliati Jorge Vicent Carolina Tenjo

A new fluorescence retrieval method is proposed to support ESA's 8th Earth Explorer FLuorescence EXplorer/Sentinel-3 (FLEX-S3) candidate tandem mission. FLEX is the first mission specially dedicated to measure the Sun-Induced vegetation chlorophyll fluorescence (SIF) strongly related with the vegetation photosynthetic activity. Most hyperspectral fluorescence retrieval algorithms available in the literature are very sensitive to true reflectance modelization and/or they assume the atmospheric status as known. The proposed algorithm delivers the retrieval of full fluorescence spectrum at canopy level by using only Top Of Atmosphere (TOA) radiances from S3 and FLEX as input. Once the spatial co-registration and cross-calibration of S3 and FLEX images have been performed, the proposed method starts with (1) the atmospheric correction of TOA radiances, characterizing the state of the atmosphere, (2) performing a first estimation of fluorescence values in main oxygen absorption bands without any approximation of true reflectance spectrum, and using this fluorescence estimation to initialize a Spectral Fitting Method (SFM) to finally retrieving a full fluorescence spectrum. This proposed fluorescence retrieval method is currently being implemented at the Level-2 Retrieval Module (L2RM) of the FLEX/End-To-End Simulator (E2ES).

FLEX

Tandem

Photochemical Reflectance Index

10.1109/igarss.2015.7326362

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Citations (6)

On the surface apparent reflectance exploitation: Entangled Solar Induced Fluorescence emission and aerosol scattering effects at oxygen absorption regions

Neus Sabater Pekka Kolmonen Luis Alonso Jorge Vicent J. Moreno

Monitoring vegetation photosynthetic activity and its link with the carbon cycle at a global scale is a leading breakthrough that the scientific community has been seeking in recent years. Pursuing this goal, one of the most important advances in the last decade has been the measurement of the Solar Induced Fluorescence (SIF) at a satellite scale. Current satellite-derived SIF estimations provide SIF measured at certain specific wavelengths depending on the retrieval strategy and the instrument capabilities. However, for the time being, no global observations of the total spectrally resolved and integrated SIF signal have been yet achieved. In a near-future context, spectrally resolved SIF estimations will be provided by missions such as the FLuorescence EXplorer (FLEX) from the European Space Agency.When disentangling the total SIF contribution, emitted between 650-800 nm, from the acquired satellite signal, molecular and aerosol absorption and scattering effects must be carefully accounted for. &#160;Particularly, within the oxygen absorption features, the characterization of the aerosol scattering effects represents the most critical step prior to the SIF estimation.In the context of the FLEX/Sentinel-3 tandem mission concept, this work presents a novel technique that refines any a priori aerosol characterization process through the exploitation of the high spectral resolution surface apparent reflectance signal at the oxygen absorption regions. Within the absorption features, SIF contribution on satellite-derived surface apparent reflectance generates a characteristic peaky spectrum. However, the shape of these peaks can be simultaneously distorted through the atmospheric correction process due to inaccuracies in the aerosol characterization among other secondary sources. Inaccuracies in the estimation of aerosol optical thickness, Angstrom exponent, asymmetry of the scattering or single scattering albedo translate into characteristic distortions in the shape of the peaks in the apparent reflectance. This particular behaviour allows inferring the magnitude of the errors and correcting them. The presented technique improves the accuracy of any a priori aerosol retrieval.Authors expect this study to be also of interest to other hyperspectral missions when exploiting, at high spectral resolution, information from oxygen absorption regions.

10.5194/egusphere-egu2020-10014

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Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)

Jorge Vicent Jochem Verrelst Neus Sabater Luis Alonso Juan Pablo Rivera

Abstract. Atmospheric radiative transfer models (RTMs) are software tools that help researchers in understanding the radiative processes occurring in the Earth’s atmosphere. Given their importance in remote sensing applications, the intercomparison of atmospheric RTMs is therefore one of the main tasks to evaluate model performance and identify the characteristics that differ between models. This can be a tedious tasks that requires a good knowledge of the model inputs-outputs and generation of large databases of consistent simulations. With the evolution of these software tools, their increase in complexity bears implications towards their use in practical applications and model intercomparison. Existing RTM-specific graphical user interfaces are not optimized for performing intercomparison studies of a wide variety of atmospheric RTMs. In this paper, we present the Atmospheric Look-up table Generator (ALG) version 2.0, a new software tool that facilitates generating large databases for a variety of atmospheric RTMs. ALG facilitates consistent and intuitive user interaction to enable running model executions and storing RTM data for any spectral configuration in the optical domain. We demonstrate the utility of ALG to perform intercomparison studies and global sensitivity analysis of broadly used atmospheric RTMs (6SV, MODTRAN, libRadtran). We expect that providing ALG to the research community will facilitate the usage of atmospheric RTMs to a wide range of applications in Earth Observation.

Toolbox

MODTRAN

Table (database)

Atmospheric models

Earth system science

Atmospheric models

10.5194/gmd-2019-188

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Citations (4)

Automatic Emulator and Optimized Look-up Table Generation for Radiative Transfer Models

viXra (2020)

Luca Martino Jorge Vicent Gustau Camps‐Valls