The EnMAP (Environmental Mapping and Analysis Program) satellite, launched on 1 April 2022, is designed to provide high-resolution imaging spectroscopy data for environmental monitoring, resource management and land use mapping. The integrity and quality of the official data products are assessed by the mission's external product validation activities, which are independent of the calibration/validation activities from the ground segment.The external validation is intended to assess, monitor, and report the quality of the L1B (top-of-atmosphere radiance in sensor coordinates), L1C (top-of-atmosphere radiance in map coordinates), and L2A (surface reflectance in map coordinates) user products. This work presents an overview of the EnMAP product validation activities during the commissioning phase and the first two years of the operational phase. Radiometric, spectral, geometric, and general uniformity aspects are evaluated with scene-based analysis methods and through comparison with ground-based reference methods. We find that EnMAP's radiometric calibration is <5%, both smile and keystone are <20% of a pixel, and the Bottom-Of-Atmosphere (BOA) reflectance and Normalized Water-Leaving reflectance are well inside the mission requirements. These results confirm that the EnMAP products fulfill the mission requirements and pave the way for the scientific exploitation and use of the EnMAP products for land, water, and atmospheric applications.

Understanding the rapid adjustments of plants to high-light exposure remains challenging, as multiple excitation and de-excitation pathways are simultaneously activated. In this study, we examined carotenoid pigment conversions at the second-scale in three tree species in parallel with high temporal resolution (<1 s) in vivo fluorescence and absorption spectroscopy. Our results reveal that both β-branch (violaxanthin, antheraxanthin, zeaxanthin) and α-branch (lutein, lutein epoxide) xanthophylls exhibit remarkably fast and oscillating pool dynamics within the first 20 seconds of illumination, reaching even maximal values in that timeframe. Prompt (0–20 s) conversion of the lutein is observed at the expense of both lutein epoxide and α-carotene in certain species, while accumulation of antheraxanthin and zeaxanthin is seen both prompt (0–20 s) and slower (>30 s). Interestingly, mirror trends between whole α- and β-branch carotenoids seem to indicate balancing trends, involving dynamic precursor shifts between α- and β-carotenes. Further, we observe that quick xanthophyll changes match the kinetic trends of fitted Gaussian-modeled absorbance peaks (approx. at 520, 535, 560 nm) within the early seconds. These quick changes in photon absorption are followed by slower-triggered non-photochemical de-excitation through a particular xanthophyll, seen from the dominant 535-nm peak, and likely attributed to antheraxanthin or zeaxanthin. The quick xanthophylls conversion redistributing the excessive excitation energy while quenching fluorescence (EET phase) is shown as one of the first responses to excessive light, before regulated energy dissipation as heat is initiated. These observations invite to interpret the non-steady state conditions and their parametrization more carefully, considering different photoprotective strategies across species.

La Albufera de Valencia presenta graves problemas de eutrofización desde los años 70. Debido a su alto interés, se han hecho multitud de trabajos científicos aplicando la teledetección al estudio de la calidad de sus aguas. Sin embargo, recientes cambios como el gran crecimiento de nuevas especies de fitoplancton o las fuertes inundaciones, requieren la búsqueda de nuevos modelos para el uso de la teledetección en este lago, pues han cambiado sus propiedades ópticas. En este trabajo, utilizando datos de campo obtenidos entre 2016 y 2025, se han calibrado diferentes índices espectrales para la estimación de distintas variables biofísicas de calidad de aguas usando Sentinel-2. Las variables en estudio han sido la concentración de clorofila-a, la ficocianina, los sólidos totales en suspensión, la profundidad del Disco de Secchi y el contenido en fósforo total. Los modelos muestran NRMSE variables entre 15 y 26% y permiten tanto la elaboración de mapas de las diferentes variables como la obtención de series temporales que nos pueden proporcionar un conocimiento más profundo del estado y los cambios de la Albufera.

FLEX-E, el simulador extremo a extremo (end-to-end) de la misión tándem FLEX/S3 es una herramienta informática que simula el proceso completo de adquisición de escenas durante el desarrollo del sistema de observación (plataformas e instrumentos) y de los algoritmos de proceso. Con una arquitectura modular, incluye la simulación de la geometría de observación, un generador de escenas basado en modelos de transferencia radiativa, módulos de instrumento y algoritmos de proceso a nivel 1 (L1) y nivel 2 (L2). Durante las fases A/B (diseño preliminar) y C/D (cualificación y producción) FLEX-E ha permitido evaluar el cumplimiento de los requisitos de misión y la consolidación de los algoritmos de calibrado, corrección geométrica, co-registrado, corrección atmosférica y productos L2. Es también una herramienta clave en la fase actual, previa al lanzamiento del satélite (previsto para septiembre de 2026), en la que se prueban los procesadores operacionales, así como durante la fase de comisionado, en la que permitirá evaluar escenarios de ajuste de algoritmos L1 y L2.

The study of cyanobacterial biovolume, the relative abundance of phytoplankton in terms of biomass, using remote sensing is not common. Its estimation can be done in two ways, indirectly through the determination of the phycocyanin concentration, since it is their main pigment, or directly by determining their abundance or biovolume. This work aims to improve the expertise for the cyanobacterial biovolume directly estimation with Sentinel-2 imagery. To develop the algorithm empirically 43 georeferenced samples were collected, 20 from the sub-tropical zone and 23 from the temperate zone, which cyanobacterial biovolumes were determined. Images were resampled, atmospherically corrected with the Case2 eXtreme neuronal net and the remote sensing reflectance were extracted. The best results were retrieved with the NDB5B4, obtaining: R2 of 0.92, RMSE of 1.71 mm3 L−1 and NRMSE of 7.6%. To demonstrate its consistency and functionality, the algorithm was applied to images thorough two years, to reproduce both temporal and spatial variations of the cyanobacterial biomass. The highest values were recorded in the subtropical zone. A tail-dam asymmetry was observed in both climatic zones. In the temperate zone, the annual variation registered a minimum and a maximum annual value, while more variations were registered in the subtropical zone.

El uso de sistemas aeroportados capaces de proporcionar estimaciones del observable SIF (Solar Induced Chlorophyll Fluorescence) es una herramienta de gran versatilidad para la calibración y validación de FLEX (FLuorescence Explorer). El INTA ha implementado el sensor de fluorescencia Headwall Chlorophyll-Fluorescence Imager (CFL) en un sistema de teledetección diseñado para plataformas aéreas tripuladas, junto con un sensor VNIR (visible e infrarrojo cercano) CASI 1500i y sus sistemas auxiliares INS/GPS (Inercial y GPS). Dentro del proyecto SpaFLEX se establecieron tres zonas en diversos ecosistemas ibéricos: Doñana (Huelva), La Roda (Albacete) y Sarrión (Teruel), aportando variabilidad en la cobertura vegetal y las condiciones ambientales. La adquisición de datos se realizó en coordinación con sensores en tierra (FLOX, Piccolo, ASD) y vehículos aéreos no tripulados, lo que permitió mediciones sincronizadas y coherencia multiplataforma entre las observaciones aerotransportadas e in situ. La campaña generó con éxito un conjunto de datos único, multiescala y multiplataforma, adecuado para un análisis integrado. Estos datos proporcionan una base clave para la validación de los algoritmos FLEX y la mejora de la calidad de los productos de Nivel 2.

La fluorescencia de la clorofila inducida por el sol (SIF) y la reflectancia de la vegetación (Ref) serán productos operativos de nivel 2 que proporcionará la próxima misión Fluorescence Explorer (FLEX) de la Agencia Espacial Europea (ESA). Con el fin de cumplir con los requisitos de incertidumbre de la ESA para los productos de nivel 2, el proyecto SpaFLEX está implementando un plan integral de calibración y validación (Cal/Val) para la misión FLEX. El plan se basa en realizar mediciones fiduciales con instrumentos in situ (aerotransportados, UAV y terreno) en test-sites de variadas formaciones vegetales y gradientes de heterogeneidad espacial, estimando la incertidumbre para los valores agregados a los 300 m de píxel de FLEX. Los diferentes protocolos desarrollados en el marco de SpaFLEX se muestran en la campaña de campo realizada en la Reserva Biológica de Doñana (RBD), donde se ha calculado el valor de SIF y Ref con su incertidumbre total para el píxel FLEX en las parcelas de matorral.

To better understand and resolve the spectral dynamics underlying actual photosynthetic efficiency regulation of plants, we assessed the stress-affected green and red-edge regions for co-varying spectral behaviour in function of photosynthetic downregulation. Specifically, we explored whether variability in canopy reflectance and estimated surface absorbance spectra (450-900 nm) could reliably track actual photosynthesis traits using three indoor experiments under controlled conditions, covering both short-term (days), and longer-term (weeks to months) time scales with and without drought treatments in addition to light-driven stress, in tomato and Scots pine seedlings. Partial least squares regression (PLSR) models and their Variable Importance in Projection (VIP) scores were used to explore the associated spectral drivers of actual and maximum photochemical quantum yield (QY), non-photochemical quenching (NPQ), and the chlorophyll fluorescence ratio (SFR_R). Co-varying spectral peaks of VIP, particularly in the green hump (519-524, 531-534 and 554 nm) and red-edge (684-685, 701-705, 711-719, 739-750 nm), were repeatedly observed across experiments and traits (QY, NPQ). These subtle changes in antenna-related absorbance were found to be relatively consistent across the experiments and associated with accurate predictions of actual QY (R2 = 0.90) and NPQ (R2 = 0.89) in the case of the diurnal-based experiment, favouring only spectral variability in those parameters. We further relate this dynamic multi-peak absorbance behaviour to the redistribution of energy levels of xanthophylls and chlorophyll due to various quenched conformations in the photosynthetic apparatus. This complex spectral imprint statistically driving the photosynthesis-related response variables requires further investigation as it may trigger improvements of next-generation models of light use efficiency and photosynthesis models based on imaging spectroscopy data.

This study assessed the potential of sun-induced chlorophyll fluorescence (SIF) to estimate plant net photosynthesis (Anet) using a series of linear and non-linear light-use efficiency (LUE) models. These models incorporated chlorophyll content-based vegetation indices as proxies for the fraction of absorbed photosynthetically active radiation (FAPAR) and non-photochemical and photochemical quenching-related vegetation indices or reflected radiance based biophysical variables as proxies for LUE. A spectral unmixing technique was employed to retrieve the fluorescence quantum efficiency (FQE) and the flux of photons absorbed by beta-Carotene and xanthophyll pigments (APAR-CarbXan), key drivers of non-photochemical quenching (NPQ). In this study, the maximum photosystem II efficiency (ΦPSII) ranged from 0.10 to 0.40, indicating a low level of photosynthetic performance under the observed conditions. In these conditions, the NPQ exhibited a high level of activation, which controlled the light reaction energy dissipation pathway and broke the positive linear relationship between photochemistry and fluorescence. Therefore, in this study, linear models incorporating FQE and APAR-CarbXan or their combination with meteorological variables failed to accurately capture the seasonal variations in Anet. However, the inclusion of a non-linear relationship between LUE and FQE significantly improved model performance, demonstrating the necessity of non-linear models for accurate SIF-based photosynthesis estimation.

There is a consensus on the role of protein conformational changes within the photosynthetic antenna that alter the spectral properties of the embedded pigments during regulated heat dissipation, but despite this, the molecular mechanisms involved are still poorly understood. The mechanisms, associated with the quenching of excessive energy, are however commonly seen in vitro as 'red spectral forms' of Chlorophyll a or red-shifted and broadened absorbance behaviour. Similar mechanisms are expected to occur in vivo, but so far, the spectral absorbance changes have not been described in detail at the whole plant canopy level. Here we derive the dynamic changes in surface absorbance features from canopy reflectance of tomato plants (Solanum lycopersicum L.), under increasing light exposure and drought. Specific features in the green (520 nm-peak) and the red-edge (695 nm-peak) region could indicate the quick activation of quenched conformational states under low light conditions, for all plant canopies. Under additional drought stress, further red-shifted and broadened absorbance changes appear, suggesting another conformational change. The latter changes disappeared upon drought recovery. Observing these antenna-related mechanisms from proximal sensing demonstrates the promising potential of imaging spectroscopy to detect the stepwise tuning of regulated energy dissipation of plants in a non-destructive way.

Sentinel-2 es una misión satelital del programa Copernicus que ofrece imágenes de 10 m de resolución espacial cada cinco días. Numerosos estudios han demostrado que es adecuado para la estimación de calidad de aguas en lagos y embalses. En este trabajo se estudian 7 embalses españoles de aguas claras de la cuenca del Júcar (Alarcón, Benagéber, Contreras, María Cristina, Regajo, Sitjar y Tous) en los que se han medido distintas variables, entre otras, la clorofila-a (Chl-a), los sólidos en suspensión (TSS), la profundidad de Disco de Secchi (SDD) y la ficocianina (PC). Con estos datos, junto a los espectros de reflectividad obtenidos de imágenes Sentinel-2 nivel L2A, es decir, con la corrección atmosférica que realiza la Agencia Espacial Europea, se han estudiado diferentes índices espectrales. Los resultados muestran que la PC se puede estimar con un índice NDI con las bandas B3 (560 ±17 nm) y B2 (490 ±32 nm), y un ajuste lineal; el SDD se puede obtener mediante un ajuste exponencial de un índice que combina las bandas B2, B3 y B4 (665 ±15 nm) y los TSS se pueden estimar con una relación lineal con un índice que combina las bandas B1 (443 ±10 nm), B2 y B3. Sin embargo, para la Chl-a no se ha encontrado un modelo único para todos los embalses, por lo que se han separado en dos grupos en función de su respuesta espectral. Para un grupo de embalses el modelo que da mejores resultados usa una combinación lineal de B2, B3 y B4 y en el otro se usa un índice tribanda, con las mismas bandas. Estos modelos permiten estimar la calidad del agua de estos embalses, mostrando tanto su distribución espacial como series temporales. Todo ello con un procesado sencillo y rápido que se puede hacer en la nube con las herramientas gratuitas de Copernicus.

Imaging spectroscopy has been a recognized and established remote sensing technology since the 1980s, mainly using airborne and field-based platforms to identify and quantify key bio- and geo-chemical surface and atmospheric compounds, based on characteristic spectral reflectance features in the visible-near infrared (VNIR) and short-wave infrared (SWIR). Spaceborne missions, a leap in technology, were sparse, starting with the CHRIS/PROBA and EO1/Hyperion missions in the early 2000s, and providing spectroscopy data with limited spectral coverage and/or low data quality in the SWIR. Since 2019, several countries and agencies have successfully launched a number of spaceborne imaging spectroscopy systems into orbit or deployed them on the International Space Station (ISS) such as DESIS, PRISMA, HISUI, GF-5, EnMAP and EMIT. Among these recent missions, the German Environmental Mapping and Analysis Program (EnMAP) stands for its long-term development, sophisticated design with on-board calibration, high data quality requirements, and extensive accompanying science program. EnMAP was launched in April 2022 and, following a successful commissioning phase, started its operational activities in November 2022. The EnMAP mission encompasses global coverage from 80 degrees N to 80 degrees S through on-demand data acquisitions. Data are free and open access with 30 m spatial resolution, a high spectral resolution with a spectral sampling distance of 6.5 nm and 10 nm in the VNIR and SWIR regions respectively, and a high signal-to-noise ratio. In this paper, we aim to present the mission's current status, coverage, science capabilities and performance two years after launch. We show the potential of EnMAP for space-based imaging spectroscopy to operate in various environments, including high and low light levels, dense forests, Antarctic glaciers, and arid agricultural areas. EnMAP enables various applications in fields such as agriculture and forestry, soil compositional, raw materials, and methane mapping, as well as water quality assessment, and snow and ice properties. The results show that EnMAP's performance exceeds the mission requirements, and highlights the significant potential for contribution to scientific exploitation in various geo- and biochemical sciences. EnMAP is also expected to serve as a key tool for the development and testing of data processing algorithms for upcoming global operational missions.

Current and future vegetation imaging spectroscopy satellites will bring a new data stream of information, of high scientific value to refine existing remote sensing products, and develop new ones. The sensors on board ESA's Fluorescence Explorer (FLEX) will cover the entire 500-780 nm range, designed to track the photosynthetic energy partitioning based on the key pigment players in the light reactions. To quantify the actual photosynthetic efficiency unambiguously, the dynamic pigment absorption behavior is crucial to complement the fluorescence information. An important role is given by the xanthophylls, regulating the non -photosynthetic quenching (NPQ) behavior which affects the 500-600 nm range. Therefore, this work focused on the development of a non -negative least squares (NNLS) spectral unmixing algorithm for reflectance (500-780 nm) retrieving the effective absorbance of individual pigments, i.e., Chlorophyll (Chl) a and b, beta -Carotene and xanthophylls. The NNLS fitting was applied to fit the total effective absorbance at leaf level, linearly composed of pigment and background absorption coefficient spectra. The model succeeded to obtain spectral fitting errors generally below 20% across the 500-780 nm range. Further, we focused on the further use of the effective absorbance by Chlorophyll a to calculate the absorbed photosynthetically active radiation or APAR Chl a. This product was combined with the total emitted fluorescence flux (670-780 nm), expressed in photon flux units, to obtain the fluorescence quantum efficiency (FQE), capturing the stress -related fluorescence quenching in the light reactions. Finally, we applied the leaf -based algorithm to foreseen FLEX image products simulated by the FLEX End -to -End Scene Generator. We were able to retrieve APAR Chl a with a RMSE of 85.5 mu mol m- 2 s- 1 (NNLS with additional upper fitting constraints) and 158.2 mu mol m- 2 s- 1 (regular NNLS), and FQE retrievals could be obtained with an R2 of 0.93 and 0.90, respectively. While the subtle xanthophyll absorption could be meaningfully fitted at the leaf scale, further improvements to the algorithms and an understanding of the physiological mechanisms are needed to deal with the complexity at larger scales. Given several challenges to be overcome, the proposed bottom -up strategy using specific pigment absorbance unmixing for (imaging) spectroscopy demonstrates the ongoing developments to complement the fluorescence product, with the aim to provide an unambiguous estimate on the actual carbon sequestration of vegetation.

Precise knowledge of cropland productivity is relevant for farmers to enable optimizing managing practices; particularly with the perspective of anticipating crop yield ahead of harvest. The current availability of high spatiotemporal resolution Sentinel-2 satellite data offers a unique opportunity to monitor croplands over time. In this context, the recently introduced kernel NDVI (kNDVI) statistically optimizes the conventional NDVI formulation by applying a nonlinear function to the involved bands, and so maximizes the spectral information extraction. This study proposes a workflow for within-field yield forecasting from Sentinel-2 kNDVI time series analysis focusing on winter cereal croplands in Switzerland over three years, comparing with NDVI as baseline. For a temporally continuous modelling of crop yields, Gaussian Process Regression (GPR) was applied to reconstruct cloud-free time series of the complete crop growing seasons. Following, distinct machine learning regression models (GPR, Kernel Ridge Regression and Random Forest) were developed to forecast yield at any point in time throughout the cropland growing season. The integration of Growing Degree Days (GDD) information as temporal spacing reference of the time series considerably improved the accuracy and consistency of in-season yield forecasting. Training and testing within the same year demonstrated that yield can be accurately forecast approximately 2–2.5 months ahead of harvest, at crops’ anthesis (flowering) phase, with an RMSE up to 0.71 t/ha and a relative RMSE of 7.60%. Although the forecasting accuracy of the models decreased when predicting yield for the unseen years, still satisfactory results were obtained: RMSE = 0.97 t/ha, relative RMSE = 11.47%.

Early stress detection of crops requires a thorough understanding of the signals showing the very first symptoms of the alterations in the photosynthetic light reactions. Detection of the activation of the regulated heat dissipation mechanism is crucial to complement passively induced fluorescence to resolve ambuiguities in energy partitioning. Using leaf spectroscopy, we evaluated the capability of pigment spectral unmixing to calculate the fluorescence quantum efficiency (FQE) and simultaneously retrieve fast absorption changes in a drought and nitrogen deficiency experiment with tomato. In addition, active fluorescence measurements and pigment analyses of xanthophylls, carotenes and chlorophylls were conducted. We observed notable responses in noninvasive proximal sensing-retrieved FQE values under stress, but as expected, these alone were not enough to identify the constraints in photosynthetic efficiency. Reflectance-based detection of the 535-nm peak absorption change was able to complement FQE and indicate the activation of regulated heat dissipation for both stress treatments under growing light conditions. However, further complexity in the light harvesting energy regulation needs to be accounted for when considering additional light stress. Our results underscore the potential of complementary in vivo quantitative spectroscopy-based products in the early and nondestructive stress diagnosis of plants, marking the path for further applications.

The European Space Agency's FLuorescence EXplorer-Sentinel 3 (ESA FLEX-S3) mission, scheduled for launch in 2026, aims to remotely detect vegetation fluorescence at 300x300-meter pixel resolution. The ESA requires a national Calibration and Validation (Cal/Val) plan for FLEX-S3 products that addresses the selection of test sites, measurement protocols, and uncertainty budgets. Despite Spain's significant Cal/Val test sites, it lacks a permanent instrumented site in international networks. The SpaFLEXImp initiative aims to implement a FLEX Cal/Val plan, standardizing protocols, and establishing a coordinated network of sites. Led by the National Institute of Aerospace Technology (INTA), the project involves the University of Valencia and the Donana Biological Station-CSIC. With a long experience in in situ, airborne, and spaceborne measurements, the teams will conduct specific Cal/Val campaigns in 3 sites, making Spain a European and international reference for terrestrial Cal/Val activities.

&lt;p&gt;Under the current climate change conditions, the early stress detection of crops and worldwide vegetation are crucial to promote sustainable agriculture and ecosystem management. With the upcoming European Space Agency&amp;#8217;s Fluorescence Explorer-Sentinel 3 (FLEX-S3) tandem mission, vegetation fluorescence and the auxiliary parameters/traits needed to interpret solar-induced vegetation fluorescence (SIF) will become available at 300x300 m spatial resolution. Today, a variety of SIF-specialized UAS systems exist to retrieve the canopy-emitted SIF over larger areas, e.g., as a reference for airborne imaging SIF sensors. However, they lack the complementary sensors needed for a correct interpretation of the highly dynamic fluorescence emission. &amp;#160;In this study we present the FluoCat system, a unique UAS system which can be mounted either in a UAV or cable-suspended mobile platform. On board the FluoCat are mounted: a high-spectral resolution Piccolo Doppio dual spectrometer system, a MAIA-S2 multispectral camera and a TeAx Thermal Capture Fusion camera, which can be triggered simultaneously according to a pre-set protocol. The FluoCat system mimics the FLEX-S3 sensor configuration, by using a multi-sensor system integrating the visible, NIR and thermal spectral regions providing complete datasets to assess the actual vegetation stress. In this context a field campaign was conducted in the experimental site &amp;#8216;Las Tiesas&amp;#8217; in Barrax, Spain, with the aim to (1) apply sampling protocols to obtain spatially representative canopy reflectance and SIF measurements, and (2) provide accurate ground truth measurements for real (i.e., leaf) surface reflectance and effective surface fluorescence measurements, linkable to the real photosynthetic performance. Further we demonstrate the development of a sensor synergy product, combining canopy physiological and structural information to reveal real surface physiological stress-related energy emission. The &amp;#8216;sunlit green fluorescence&amp;#8217; is a synergy product combining the top-of-canopy fluorescence and the fractional vegetation cover of the sunlit vegetation. This synergy product improved the estimation of the effective surface fluorescence flux, using the leaf fluorescence emission as reference, by reducing the errors from 36 % to 18 % (band 687 nm); and from 24 % to 6 % (band 760 nm). Real surface properties and products referring to the actual photosynthetic surface behavior are promising quantitative proxies to assess the impact of climate change and/or management practices on crop lands or even whole ecosystems. With this study we show how innovative proximal sensing platforms can help to develop new data processing schemes combining all required information for the quantitative assessment of vegetation health, even before visible damage occurs. The further processing and normalization of first-derived stress proxies such as SIF can generate further in-depth early stress detection, directly related to the photosynthetic light reactions, and further global carbon assessment. These developments are in direct support for the global monitoring of early vegetation stress under a changing global climate.&lt;/p&gt;

Background Mediterranean shrublands are composed of species that have different regeneration strategies after fire and soil seed bank types. However, differences over the years in seed dispersal temporal and spatial patterns of the various plants composing a community have been little investigated. Here, we studied the temporal and spatial patterns of seed dispersal in four shrubs of an old (> 40 years) shrubland in central Spain. Three of them are seeders ( Cistus ladanifer , Erica umbellata , and Salvia rosmarinus ), and one is a resprouter ( Erica arborea ); the first two have persistent soil seed banks, and the latter two, transient. A 15 × 10 m plot was chosen and divided into a 0.5 × 0.5 m grid, where plant cover and density were measured. At 106 quadrats, seed traps were set and periodically (1–2 monthly) monitored for 3 years. Results S. rosmarinus dispersed in late spring-early summer, E. arborea dispersed during the summer, and C. ladanifer and E. umbellata dispersed from early summer to nearly late spring of the next year. Globally, seeds were being dispersed all year round. The seed crop size of a given species varied between years, although species differed in the year their seed crop was largest, despite large differences in climate. Seed rain and plant cover of each species were poorly related in terms of the variance explained by the models. Semivariogram analysis showed that seed dispersal expanded beyond that of the plant cover of each species by a few meters. No association between seed crop size and spatial dependence was ascertained. While species dispersal in space tended to be negatively related to one another, E. arborea seeds tended to dominate underneath the majority of the other species. Conclusions S. rosmarinus dispersed before the fire season, which is consistent with seeds avoiding fire while on the plant; C. ladanifer and E. umbellata dispersed mostly after the fire season, which is coherent with a bet-hedging strategy against seed predators; E. arborea dispersed before the rainy season, which is expected for a plant that germinates readily after imbibition. Seed dispersal in time was compatible with the type of soil seed bank and post-fire regeneration of the species. The evidence of such a relationship with spatial patterns was weak. The dominance of E. arborea seeds underneath most of the other species suggests that this mid-successional species might dominate when openings form due to the deaths of standing plants of the seeders between two fires, given their lower longevity.

With the upcoming Fluorescence Explorer (FLEX) satellite mission from the European Space Agency, vegetation fluorescence (650–780 nm) will become available at 300x300 m resolution. Calibration and validation strategies of the fluorescence (F) signal remain however challenging, due to (1) the radiometric subtlety of the signal, (2) the multiple entangled drivers of the signal in space and in time, and (3) the need of a spatially representative acquisition, considering the previous two points. To tackle these challenges, the present work introduces the FluoCat, a cable-suspended system for the proximal sensing indirect measurement of solar-induced fluorescence, mounted across an agricultural field, covering a 60-m transect. On board the FluoCat are mounted: a high-spectral resolution Piccolo Doppio dual spectrometer system, a MAIA-S2 multispectral camera and a TeAx Thermal Capture Fusion camera, which can be triggered simultaneously according to a pre-set protocol. In order to test the system, two protocols were evaluated, a point-wise protocol, stopping at a pre-determined points to acquire the measurements, and the swiping protocol, acquiring measurements while in movement along the transect. Taking as a reference the values obtained with the swiping protocol, which captures the higher spatial variability, it was found that to achieve an averaged mean absolute percentage error (MAPE) below 2 % within between the spectral range of 500–800 nm, it is required a minimum of 6 sampling points to characterize the spectral variability of the 40-m melon crop transect. Further, by combining the fluorescence products of the Piccolo system normalized by PAR (NormF687, NormF760) and the fractional cover of sunlit vegetation (FVC Sunlit) obtained from the MAIA, we developed a multi-sensor product, i.e., the 'sunlit green F' for both retrieved bands. This synergy product improved the estimation of the effective surface fluorescence flux, with the leaf fluorescence emission as reference, by reducing the errors from 36 % to 18 % (band 687 nm); and from 24 % to 6 % (band 760 nm).