Towards the quantitative and physically-based interpretation of solar-induced vegetation fluorescence retrieved from global imaging

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

Potential of the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor for the monitoring of terrestrial chlorophyll fluorescence

Global monitoring of sun-induced chlorophyll fluorescence (SIF) is improving our knowledge about the photosynthetic functioning of terrestrial ecosystems. The feasibility of SIF retrievals from spaceborne atmospheric spectrometers has been demonstrated by a number of studies in the last years. In this work, we investigate the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite mission for SIF retrieval. TROPOMI will sample the 675–775 nm spectral window with a spectral resolution of 0.5 nm and a pixel size of 7 km × 7 km. We use an extensive set of simulated TROPOMI data in order to assess the uncertainty of single SIF retrievals and subsequent spatio-temporal composites. Our results illustrate the enormous improvement in SIF monitoring achievable with TROPOMI with respect to comparable spectrometers currently in-flight, such as the Global Ozone Monitoring Experiment-2 (GOME-2) instrument. We find that TROPOMI can reduce global uncertainties in SIF mapping by more than a factor of 2 with respect to GOME-2, which comes together with an approximately 5-fold improvement in spatial sampling. Finally, we discuss the potential of TROPOMI to map other important vegetation parameters at a global scale with moderate spatial resolution and short revisit time. Those include leaf photosynthetic pigments and proxies for canopy structure, which will complement SIF retrievals for a self-contained description of vegetation condition and functioning

Design of a generic end-to-end mission performance simulator and application to the performance analysis of the FLEX/Sentinel-3 mission

La Observación de la Tierra mediante técnicas de teledetección con instrumentos ópticos en satélite tiene como objetivo monitorizar los procesos bio-geofísicos en la superficie y atmósfera terrestre, adquiriendo datos a diferentes longitudes de onda del espectro electromagnético. Con el fin de asegurar el mantenimiento de las observaciones y las capacidades para entender el sistema Tierra, nuevas misiones satelitales están siendo desarrolladas por agencias espaciales nacionales e internacionales así como organizaciones de investigación. En este contexto, los simuladores de misiones espaciales (E2ES por sus siglas en inglés, End-to-End Mission Performance Simulator) ofrecen a los científicos e ingenieros un marco único para entender el impacto de la configuración del instrumento en los productos finales de la misión y, por tanto, acelerar el desarrollo de una misión desde la fase conceptual hasta el lanzamiento. Al mismo tiempo, estas herramientas permiten definir una metodología para la consolidación de los requisitos y la evaluación de la actuación de estas misiones satelitales, estableciendo criterios para la selección de una misión por las diferentes agencias espaciales. Mientras que el concepto de un E2ES es simple, el diseño de nuevos E2ES y la evolución de los ya existentes tienen una falta de guias y metodología estandarizadas, lo cual se traduce en un caro y complejo proceso de re-ingeniería. Esta tesis cubre dos objetivos principales. Por un lado, se pretende armonizar el trabajo hecho en el campo de los E2ES durante las últimas décadas y proponer una serie de guias y metodologías para desarrollas E2ES para misiones satelitales futuras con instrumentos ópticos pasivos. El primer objetivo es por tanto "Diseñar un simulador de misión genérico que pueda ser fácilmente adaptado para reproducir la mayoría de misiones satelitales, presentes y futuras, con sensores ópticos pasivos". Por otro lado, la misión FLEX/Sentinel-3 de la ESA se usa para validar, a través de la implementación de su propio E2ES, el diseño de la arquitectura genérica tratada en el punto anterior. De este modo, el E2ES para la misión FLEX permite evaluar la actuación de la misión para la obtención de la fluorescencia inducida por radiación solar emitida por la vegetación terrestre. La misión FLEX/Sentinel-3 es una candidata óptima para esta tarea de validación dada la complejidad de la misión (p.ej. vuelo en tandem, multi-plataforma/-instrumento, múltiples rangos y resoluciones espectrales, observaciones multi-angulares, sinergia de productos). El segundo objetivo de esta tesis es por tanto "Evaluar la misión FLEX para la la observación de la emisión de fluorescencia emitida por la vegetación usando un E2ES desarrollado de acuerdo con una arquitectura genérica". La razón fundamental tras esta Tesis es promocionar el uso de una arquitectura genérica común para los E2ES que permita comparar misiones satelitales en procesos de selección competitiva como los Earth Explorer de la ESA así como acelerar el análisis de los requisitos técnicos y el rendimiento de la misión a nivel científico. Particularmente, esto se muestra mediante la implementación de esta arquitectura genérica para el caso específico de la misión FLEX/Sentinel-3 demostrando que: (1) la misión es capaz de obtener con la precisión requerida la emisión de fluorescencia por la vegetación ; y (2) el concepto de esta arquitectura genérica es apto para reproducir la complejidad de la misión FLEX/Sentinel-3 y por tanto se espera que esta metodología pueda ser también aplicable para un gran abanico de misiones ópticas pasivas. Esta base lógica se consigue a partir de una categorización de varias misiones satelitales y la identificación y análisis de los elementos principales que afectan en el rendimiento de la misión e impactan en la arquitectura de un simulador de misión. La arquitectura genérica para E2ES propuesta se valida mediante la implementación del E2ES de la misión FLEX/Sentinel-3 de la ESA teniendo en cuenta ambos satélites, sus instrumentos, y evaluando con este E2ES el rendimiento de la misión FLEX. En esta Tesis, los capítulos 1 y 2 introducen los principales temas de esta Tesis y definen los conceptos básicos. Los capítulos 3 al 5 describe el diseño de la arquitectura genérica para los E2ES en misiones ópticas pasivas. Finalmente, el capítulo 6 resume los principales resultados y las conclusiones derivadas de esta Tesis.Earth observation by satellite optical remote sensing aims to monitor bio-geophysical processes happening in the Earth surface and the atmosphere by acquiring data at different wavelengths of the electromagnetic spectrum. In order to ensure sustained observations and capabilities to fill scientific gaps in our current understanding of the Earth system, new satellite missions are being developed by national and international space agencies and research organisations. In this context, End-to-End Mission Performance Simulator (E2ES) tools offer scientists and engineers a unique framework to understand the impact of instrument configuration in the final mission products and to accelerate the mission development from concept to deployment. At the same time, these cost-effective and flexible tools are capable of defining a methodology for the consolidation of requirements and performance assessment of these new satellite missions, setting the criteria for mission selection by the various space agencies’ programme boards. While the concept of an E2ES is simple, the design of new E2ES and the evolution of existing ones lack from a standard methodology and guidelines, which translates into a complex and costly re-engineering process. This Thesis covers two main objectives. On the one hand, it aims to harmonize the work done in the field of E2ES during the last decades and to propose a set of guidelines or methodology to develop E2ES for future remote sensing satellite passive optical missions. The first main objective, therefore, is: ’To design a generic end-to-end mission performance simulator that can be easily adapted to reproduce most present or future passive optical spaceborne instruments’. On the other hand, the ESA’s FLEX/Sentinel-3 tandem mission is used to validate, through the implementation of its E2ES, the designed generic E2ES architecture and to evaluate the performance of the FLEX mission for the retrieval of Sun-induced fluorescence. The FLEX/Sentinel- 3 mission is optimally suitable for this validation task due to the complexity of the mission (e.g. tandem flight, multi-platform/-instrument mission, multiple spectral ranges and resolutions, multi-angular observations, synergy of products). The second main objective, therefore, is: ’To evaluate the FLEX mission for Sun-induced fluorescence retrievals using a newly developed E2ES in agreement with the designed generic E2ES architecture.’. The rationale behind this Thesis is promoting the use of a common generic E2ES architecture that allows comparing missions in competitive selection process (e.g., ESA’s Earth Explorers) and speeding-up the analysis of the mission technical requirements and scientific performances. Particularly, this is shown by implementing this generic E2ES architecture for the specific case of FLEX/Sentinel-3 mission demonstrating that: (1) the mission is capable of retrieving Sun-induced fluorescence within the required accuracy; and (2) the conceptual generic E2ES architecture is suitable toreproduce the complexity of the FLEX/Sentinel-3 tandem mission and thus it is expected to be also applicable for a wide range of passive optical missions. This rationale is achieved by categorising several satellite missions to identify and analyse the main elements that affect the mission performance and impact the simulator architecture. The proposed generic E2ES architecture is validated by implementing the ESA’s FLEX/Sentinel-3 E2ES, both satellites and their instruments, and testing it through the performance assessment of the FLEX mission products. In this Thesis, Chapters 1 and 2 introduce the main research questions and sets the background concepts. Then Chapters 3–5 describe the design of a generic E2ES architecture for passive optical missions. Finally, Chapter 6 summarizes the main results and conclusions derived in this Thesis

Development of atmospheric correction algorithms for very high spectral and spatial resolution images: application to SEOSAT and the FLEX/Sentinel-3 missions

Advanced high spectral and spatial resolution imager spectrometers on board new generation of Earth Observation missions bring new exciting opportunities to the remote sensing scientific community. However, this progress goes hand in hand with new challenges. The exploitation of data acquired from these family of advanced instruments requires new processing algorithms able to deal with these particularities. As part of this evolution, atmospheric correction algorithms - a mandatory processing step applied prior to the Earth surface reflectance data exploitation - must be adapted or reformulated, thereby paying special attention to how atmospheric effects disturb the acquired signal in the spectral and spatial domains. For these reasons, this Thesis aims to develop new atmospheric correction strategies to be applied over very high spectral and spatial resolution data. Following this goal, this Thesis was conducted in the framework of two missions during their development phase: (1) the FLEX/Sentinel–3 tandem space mission (for high spectral resolution data) and, (2) the Ingenio/SEOsat space mission (for high spatial resolution data). In the context of these missions, an additional challenge is introduced when acquiring proximal remote sensing data for their validation. This is especially relevant for the FLEX mission, which is dedicated to monitor the weak Solar Induced Chlorophyll Fluorescence (SIF) signal. Following this motivation, the main objectives of this Thesis are threefold: The first objective involved to analyse atmospheric effects on the Ingenio/SEOsat high spatial and low spectral resolution satellite mission and to propose a new atmospheric correction strategy. This strategy was called Hybrid and combines: (1) a per–pixel atmospheric radiative transfer model inversion technique making use of auxiliary data to characterize the atmospheric state, followed by (2) an image deconvolution technique modelling the atmospheric MTF to correct for atmospheric spatial effects. The Hybrid method was applied to Sentinel–2 data, particularly over bands acquired at 10 m resolution due to its similarities with the Ingenio/SEOsat mission. The second objective involved to define a novel atmospheric correction strategy for the FLEX/Sentinel-3 tandem mission. The proposed strategy is a two-steps method where information from Sentinel-3 instruments, OLCI and SLSTR, is first used in synergy to characterize the aerosol and water vapour presence. The high spectral resolution of FLEX data is subsequently exploited to refine the previously aerosol characterization. As part of this objective, the suitability of all the approximations assumed in the formulation proposed for the atmospheric inversion of FLEX data was validated against the FLEX mission requirements. The third objective involved to develop a strategy that deals with the atmospheric correction of very high spectral and spatial resolution data acquired at lower atmospheric scales such as Unmanned Aerial Vehicles or systems mounted on towers. In this Thesis, it was demonstrated that even when acquiring the signal at proximal remote sensing scale, i.e., few meters from the target oxygen absorption must be compensated to properly estimate SIF within these spectral regions. For this reason, a strategy to compensate for the oxygen absorption while properly dealing with the instrumental spectral response function convolution was presented and tested using simulated data. Altogether, this work identified challenges associated to atmospheric correction when applying to high spatial and especially to very high spectral resolution data. In this Thesis, adequate formulations have been developed to resolve these difficulties, and successful methodologies have been designed for the particular cases of SEOsat (high spatial resolution) and FLEX (high spectral resolution); two future remote sensing space missions that will be launched in the forthcoming years

Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine

Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping of essential vegetation traits from Sentinel-3 (S3) imagery. The traits included leaf chlorophyll content (LCC), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and fractional vegetation cover (FVC), being fundamental for assessing photosynthetic activity on Earth. The workflow involved Gaussian process regression (GPR) algorithms trained on top-of-atmosphere (TOA) radiance simulations generated by the coupled canopy radiative transfer model (RTM) SCOPE and the atmospheric RTM 6SV. The retrieval models, named to S3-TOA-GPR-1.0, were directly implemented in Google Earth Engine (GEE) to enable the quantification of the traits from TOA data as acquired from the S3 Ocean and Land Colour Instrument (OLCI) sensor. Following good to high theoretical validation results with normalized root mean square error (NRMSE) ranging from 5% (FAPAR) to 19% (LAI), a three fold evaluation approach over diverse sites and land cover types was pursued: (1) temporal comparison against LAI and FAPAR products obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) for the time window 2016–2020, (2) spatial difference mapping with Copernicus Global Land Service (CGLS) estimates, and (3) direct validation using interpolated in situ data from the VALERI network. For all three approaches, promising results were achieved. Selected sites demonstrated coherent seasonal patterns compared to LAI and FAPAR MODIS products, with differences between spatially averaged temporal patterns of only 6.59%. In respect of the spatial mapping comparison, estimates provided by the S3-TOA-GPR-1.0 models indicated highest consistency with FVC and FAPAR CGLS products. Moreover, the direct validation of our S3-TOA-GPR-1.0 models against VALERI estimates indicated good retrieval performance for LAI, FAPAR and FVC. We conclude that our retrieval workflow of spatiotemporal S3 TOA data processing into GEE opens the path towards global monitoring of fundamental vegetation traits, accessible to the whole research community.We gratefully acknowledge the financial support by the European Space Agency (ESA) for airborne data acquisition and data analysis in the frame of the FLEXSense campaign (ESA Contract No. 4000125402/18/NL/NA). The research was also supported by the Action CA17134 SENSECO (Optical synergies for spatiotemporal sensing of scalable ecophysiological traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu, accessed on: 8 January 2022). This publication is also the result of the project implementation: “Scientific support of climate change adaptation in agriculture and mitigation of soil degradation” (ITMS2014+313011W580) supported by the Integrated Infrastructure Operational Programme funded by the ERDF

Potential of the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor for the monitoring of terrestrial chlorophyll fluorescence

Global monitoring of sun-induced chlorophyll fluorescence (SIF) is improving our knowledge about the photosynthetic functioning of terrestrial ecosystems. The feasibility of SIF retrievals from spaceborne atmospheric spectrometers has been demonstrated by a number of studies in the last years. In this work, we investigate the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite mission for SIF retrieval. TROPOMI will sample the 675–775 nm spectral window with a spectral resolution of 0.5 nm and a pixel size of 7 km × 7 km. We use an extensive set of simulated TROPOMI data in order to assess the uncertainty of single SIF retrievals and subsequent spatio-temporal composites. Our results illustrate the enormous improvement in SIF monitoring achievable with TROPOMI with respect to comparable spectrometers currently in-flight, such as the Global Ozone Monitoring Experiment-2 (GOME-2) instrument. We find that TROPOMI can reduce global uncertainties in SIF mapping by more than a factor of 2 with respect to GOME-2, which comes together with an approximately 5-fold improvement in spatial sampling. Finally, we discuss the potential of TROPOMI to map other important vegetation parameters at a global scale with moderate spatial resolution and short revisit time. Those include leaf photosynthetic pigments and proxies for canopy structure, which will complement SIF retrievals for a self-contained description of vegetation condition and functioning

OLCI-A/B tandem phase: evaluation of FLuorescence EXplorer (FLEX)-like radiances and estimation of systematic differences between OLCI-A and OLCI-FLEX

During the tandem phase of Sentinel-3A and Sentinel-3B in summer 2018 the Ocean and Land Colour Imager (OLCI) mounted on the Sentinel-3B satellite was reprogrammed to mimics ESA's eighth Earth Explorer, the FLuorescence EXplorer (FLEX). The OLCI in FLEX configuration (OLCI-FLEX) had 45 spectral bands between 500 and 792 nm. The new data set with high-spectral-resolution measurements (bandwidth: 1.7–3.7 nm) serves as preparation for the FLEX mission. Spatially co-registered measurements of both instruments are used for the atmospheric correction and the retrieval of surface parameters, e.g. the fluorescence or the leaf area index. For such combined products, it is essential that both instruments are radiometrically consistent. We developed a transfer function to compare radiance measurements from different optical sensors and to monitor their consistency. In the presented study, the transfer function shifts information gained from high-resolution “FLEX-mode” settings to information convolved with the spectral response of the normal (lower) spectral resolution of the OLCI sensor. The resulting reconstructed low-resolution radiance is representative of the high-resolution data (OLCI-FLEX), and it can be compared with the measured low-resolution radiance (OLCI-A measurements). This difference is used to quantify systematic differences between the instruments. Applying the transfer function, we could show that OLCI-A is about 2 % brighter than OLCI-FLEX for most bands of the OLCI-FLEX spectral domain. At the longer wavelengths (> 770 nm) OLCI-A is about 5 % darker. Sensitivity studies showed that the parameters affecting the quality of the comparison of OLCI-A and OLCI-FLEX with the transfer function are mainly the surface reflectance and secondarily the aerosol composition. However, the aerosol composition can be simplified as long as it is treated consistently in all steps in the transfer function. Generally, the transfer function enables direct comparison of instruments with different spectral responses even with different observation geometries or different levels of observation. The method is sensitive to measurement biases and errors resulting from the processing. One application could be the quality control of the FLEX mission; presently it is also useful for the quality control of the OLCI-FLEX data

Sentinel-3/FLEX Biophysical Product Confidence Using Sentinel-2 Land-Cover Spatial Distributions

The estimation of biophysical variables from remote sensing data raises important challenges in terms of the acquisition technology and its limitations. In this way, some vegetation parameters, such as chlorophyll fluorescence, require sensors with a high spectral resolution that constrains the spatial resolution while significantly increasing the subpixel land-cover heterogeneity. Precisely, this spatial variability often makes that rather different canopy structures are aggregated together, which eventually generates important deviations in the corresponding parameter quantification. In the context of the Copernicus program (and other related Earth Explorer missions), this article proposes a new statistical methodology to manage the subpixel spatial heterogeneity problem in Sentinel-3 (S3) and FLuorescence EXplorer (FLEX) by taking advantage of the higher spatial resolution of Sentinel-2 (S2). Specifically, the proposed approach first characterizes the subpixel spatial patterns of S3/FLEX using inter-sensor data from S2. Then, a multivariate analysis is conducted to model the influence of these spatial patterns in the errors of the estimated biophysical variables related to chlorophyll which are used as fluorescence proxies. Finally, these modeled distributions are employed to predict the confidence of S3/FLEX products on demand. Our experiments, conducted using multiple operational S2 and simulated S3 data products, reveal the advantages of the proposed methodology to effectively measure the confidence and expected deviations of different vegetation parameters with respect to standard regression algorithms. The source codes of this work will be available at https://github.com/rufernan/PixelS3

Assessing the contribution of understory sun-induced chlorophyll fluorescence through 3-D radiative transfer modelling and field data

A major international effort has been made to monitor sun-induced chlorophyll fluorescence (SIF) from space as a proxy for the photosynthetic activity of terrestrial vegetation. However, the effect of spatial heterogeneity on the SIF retrievals from canopy radiance derived from images with medium and low spatial resolution remains uncharacterised. In images from forest and agricultural landscapes, the background comprises a mixture of soil and understory and can generate confounding effects that limit the interpretation of the SIF at the canopy level. This paper aims to improve the understanding of SIF from coarse spatial resolutions in heterogeneous canopies by considering the separated contribution of tree crowns, understory and background components, using a modified version of the FluorFLIGHT radiative transfer model (RTM). The new model is compared with others through the RAMI model intercomparison framework and is validated with airborne data. The airborne campaign includes high-resolution data collected over a tree-grass ecosystem with the HyPlant imaging spectrometer within the FLuorescence EXplorer (FLEX) preparatory missions. Field data measurements were collected from plots with a varying fraction of tree and understory vegetation cover. The relationship between airborne SIF calculated from pure tree crowns and aggregated pixels shows the effect of the understory at different resolutions. For a pixel size smaller than the mean crown size, the impact of the background was low (R2 > 0.99; NRMSE 0.2). This study demonstrates that using a 3D RTM model improves the calculation of SIF significantly (R2 = 0.83, RMSE = 0.03 mW m−2 sr−1 nm−1) when the specific contribution of the soil and understory layers are accounted for, in comparison with the SIF calculated from mixed pixels that considers only one layer as background (R2 = 0.4, RMSE = 0.28 mW m−2 sr−1 nm−1). These results demonstrate the need to account for the contribution of SIF emitted by the understory in the quantification of SIF within tree crowns and within the canopy from aggregated pixels in heterogeneous forest canopies