Conference Agenda

FLEXvalGER consists of nine scientific and two industrial partners that will validate ESA‑FLEX products over Germany during FLEX commissioning/operational phases. It combines expertise in acquiring, processing and validating in‑situ, UAV, airborne and space‑borne observations. Validation of FLEX includes: (A) direct comparison of satellite data with ground measurements, (B) indirect validation through radiative‑transfer‐model inversion, (C) inter‑comparison with other satellite products (DESIS, EnMAP, Sentinel‑5P) and (D) time‑series analysis. The network of well‑established research sites across Germany hosts dedicated infrastructure such as FloX fluorescence towers, eddy-covariance (EC) flux towers and HYPERNETS installations. The validation effort addresses agriculture and forest ecosystems, airborne and space‑borne reference data, and instrument calibration.

Agriculture: FZJ will focus on crops while deploying FloX towers (MONI/MICRO-PAMs and other validation instruments) together with complementary UAV AirFloX and HyPlant airborne hyperspectral/fluorescence flights in parallel to FLEX overpasses close to Jülich. University of Göttingen will add a 2 m FloX tower next to an EC flux tower at the Reinshof site while recording in-situ validation parameters. GFZ will carry out HySpex and FluorSpec UAV surveys together with HYPSTAR and other reference measurements at the Heydenhof site.

Forest: University of Freiburg is running a sensor-network site with continuous FloX measurements from an EC flux tower (45 m), supplemented by in-situ validation data, UAV surveys, and additional atmospheric parameter monitoring. University of Göttingen plans to integrate a FloX on the EC tower at Leinefelde site, together with in-situ validation and targeted UAV LiDAR and spectral imaging. University of Leipzig will operate a moveable crane‑mounted FloX at 40 m at the Auwald site together with in-situ validation and destructive leaf sampling measurements. GFZ will supply HYPSTAR and RoX data from a moveable canopy crane together with complementary in situ and UAV data. JKI will install low‑cost PAR/DHP sensors at the Hakel site to collect reference measurements of LAI and fAPAR, complemented by UAV LiDAR and optical imagery.

Instrumentation & cross‑mission: DLR will compare FLEX to HyPlant/HySpex/DESIS/EnMAP, validate radiometric and spectral aspects of the FLEX L1C and L2 products, and retrieves O₂‑A SIF with detailed error models, producing high‑resolution SIF maps that are down‑scaled to FLEX pixels. Maitec will contribute to SIF retrieval and a sensor‑specific uncertainty framework for all airborne/spaceborne SIF products. MPI-BGC plans to extract Sentinel‑5P/TROPOMI footprint‑level SIF and Sentinel‑2 NIRv/fesc over 10×10 km validation zones, attempting to separate radiation, structure and physiology effects, and compares with FLEX Level‑2B/L2C. JB Hyperspectral plans for on-site calibration of FloXes, equipping them with MoMo real‑time data links and running a unified processing chain feeding data into the INSIF network. Walz operates a central PAM calibration laboratory, performs regular cross‑calibrations of devices and maintains calibrated loan units to guarantee continuous fluorescence measurements.

Validated data products include almost all FLEX L1C-L2C data products with specific emphasis on in situ data for L2C product validation. Altogether, through these interlinked activities, the consortium will deliver a fully traceable, uncertainty‑quantified validation of FLEX Level‑2 products across representative agricultural and forest ecosystems in Germany.

The SpaFLEX project, funded by the Spanish Ministry of Science and Innovation, establishes a comprehensive Calibration and Validation (Cal/Val) framework for the upcoming ESA FLEX-S3 mission in Spain. Focused on Level-2 products—specifically Sun-Induced Chlorophyll Fluorescence (SIF) and reflectance—the project defines standardized sampling protocols across three diverse Spanish ecosystems: agricultural, forest, and Mediterranean dehesa. The goal is to provide accurate ground-truth data by characterizing spatial heterogeneity through a multi-scale protocol within the 300x300 meter FLEX pixel.

A core component of the project is the spatial heterogeneity characterization strategy, which optimizes the distribution of Elementary Sampling Units (ESUs) within the 300x300 meter FLEX pixel. Using Sentinel-2 biophysical products as proxies for SIF and Non-Photochemical Quenching (NPQ), the project employs a flexible framework that adapts to the structural complexity of each site. In relatively uniform ecosystems, the strategy determines the total sample size first to ensure an unbiased global distribution. In contrast, for highly fragmented landscapes, a stratification-first approach is used to ensure field measurements capture distinct vegetation classes and environmental gradients. By incorporating semivariogram analysis to account for spatial autocorrelation, this dual-flow strategy ensures that ground-truth data accurately reflect the sub-pixel variability inherent in the FLEX footprint. The uncertainty propagation of in-situ SIF and surface reflectance for the 300x300 m area representing a FLEX pixel, is performed using the Law of Propagation of Uncertainties and Monte Carlo methods.

To bridge the gap between leaf-level mechanisms and satellite observations, the SpaFLEX project implements a multi-scale approach. This integrates leaf-level measurements (FluoWat) with canopy-level continuous monitoring (FLoX, Piccolo-FluoCat) and spectroradiometric surveys (ASD FieldSpec). These ground data are scaled using UAV-based hyperspectral imaging (Cubert S185) and airborne sensors (CASI 1500i, Headwall CFL-005) to provide an integrated, representative value for the FLEX footprint.

This methodology was tested in July 2025 during a field campaign at Doñana National Park. The site features a sharp functional diversity gradient between xerophilic (Monte Blanco) and hygrophilic (Monte Negro) habitats. By applying the optimized sampling strategy, ground-based SIF and reflectance measurements were captured and upscaled to the FLEX pixel resolution using scaling factors derived from leaf area distribution and high-resolution UAV data. This study case demonstrates a statistically sound and operationally viable methodology for validating FLEX products in complex Mediterranean environments.

The FLORA project (FLEX Leaf Observation and Retrieval via Hybrid Approaches) establishes a robust calibration and validation (Cal/Val) framework for ESA’s FLEX mission, with a focus on Level-2C vegetation products, leaf area index, fAPAR, leaf chlorophyll and carotenoid content, and Level-2B Sun-Induced Fluorescence (SIF). FLORA combines hyperspectral and LiDAR observations observed from Unmanned Aerial Vehicles (UAV), ground-based SIF systems (Piccolo-Doppio, Piccolo, FLOX), and intensive leaf-level sampling across four European reference sites: 1) the Scots pine ICOS forest at NL-Loobos, 2) the complementary Speulderbos pine forest, 3) the managed grassland site at NL-Cabauw, and 4) an alfalfa cropping system in Lombardy, Italy. Each site is sampled within a 3 × 3 km window to define statistically robust Elementary Sampling Units (ESUs). Although a 900 × 900 m area corresponds geometrically to the 300 m FLEX footprint, the larger window exploits higher-resolution Sentinel-2, PRISMA and EnMAP data to characterise sub-pixel heterogeneity, delineate ESUs, and enable robust aggregation when upscaling reflectance and SIF to the FLEX scale. TROPOMI and GOME-2C SIF products support atmospheric screening, temporal consistency and inter-sensor compatibility. During the 2026–2027 growing seasons, coordinated UAV campaigns will deploy a Nano-Hyperspec sensor, LiDAR and FluorSpec/FLOX systems to acquire high-resolution reflectance, structural and SIF data around FLEX overpasses. The timing of these airborne campaigns will be dynamically adjusted to align with FLEX mission availability, ensuring optimal temporal matching between reference measurements and satellite observations. These data will be complemented by destructive and proximal sampling of chlorophyll, carotenoids, nitrogen, water content and LAI following harmonised protocols to ensure consistency across sites. A key innovation of FLORA is the development of an open, modular inversion framework combining radiative transfer models with advanced machine-learning algorithms implemented in open-source environments. This system will generate high-resolution maps of biophysical traits and SIF from UAV and satellite data, quantify uncertainties from model structure, spectral degradation and spatial aggregation, and evaluate the sensitivity of FLEX products across forest, grassland and cropland systems. The resulting multiscale datasets and inversion tools will provide a transferable.

Observations of solar induced chlorophyll fluorescence (SIF) offer strong potential to directly assess vegetation photosynthesis from leaf to canopy and up to regional and global scales. SIF signals are comprised of red and far-red emissions released from the chloroplasts as a by-product of photosynthesis. The European Space Agency's (ESA's) Fluorescence Explorer (FLEX, to be launched in the fall of 2026) is the first mission designed to measure SIF in both regions monthly at high spatial resolution (300 m) in tandem with Sentinel 3. FLEX will provide global maps of vegetation reflectance, temperature and red and far-red SIF, to improve the understanding of the way photosynthesis affects the terrestrial carbon and water cycles. This effort facilitates the calibration, validation and interpretation for the USA of the new products FLEX will produce, by meeting the project goals: 1) to characterize the dynamic seasonal relationships between canopy photosynthetic function and vegetation chlorophyll fluorescence and reflectance, as measured continuously for tundra, boreal forest, prairie, deciduous forest, and crops at flux tower sites in the USA at leaf, proximal canopy, and satellite scales; and 2) to advance the methods for modeling, interpretation and applied use of SIF and reflectance products for estimating GPP and timely detection of stress. The research contributes to the development and testing of FLEX SIF algorithms and products for typical vegetation covers in the U.S.A.

Robust automated chlorophyll fluorimeters (i.e., MONITORING-PAM, WALZ) and proximal dual spectrometers (i.e., fluorescence box or FloX, JB-Hyperspectral) are now enabling continuous diurnal and seasonal measurements of leaf chlorophyll fluorescence metrics and canopy SIF, PAR and reflectance for extended periods. Time series of such data are being collected in the USA at large, representative of the ecosystems sites in conjunction with eddy covariance measurements of gross primary productivity (GPP), field measurements of chlorophyll and leaf area index, and airborne and satellite hyperspectral and very high spatial resolution (i.e., Planet SuperDove and World View with red-edge bands) reflectance images. The Soil Canopy Observation of Photochemistry and Energy fluxes model (SCOPE) was used to integrate the collections.

We derived estimates of leaf and canopy traits characterizing canopy chlorophyll, SIF and leaf photosynthetic efficiency (electron transport rate or ETR, photochemical and non-photochemical quenching and yield to photosystem two) diurnally and across the seasons. The variation in vegetation photosynthetic function and the associated canopy traits increased with the advancement of senescence during the fall season. Using proximal measurements, we evaluated the links between chlorophyll fluorescence, reflectance and photosynthetic function at leaf and canopy levels and across the seasons. Using canopy reflectance we derived canopy traits (e.g., Cab, LAI, SIF and GPP) and implemented partial least square regression models (PLSR) for their estimation at local, regional and larger spatial scales. Using the links between leaf chlorophyll fluorescence metrics, canopy reflectance and SIF, currently we are developing approaches for upscaling leaf photosynthetic efficiency to canopy level, which is important for enabling dynamic monitoring of photosynthetic function. This study characterized the dynamics in canopy photosynthetic function, as measured at leaf, proximal canopy and satellite levels; and developed innovative algorithms for estimation of leaf ETR and canopy GPP for tundra, black spruce dominated boreal forest, tulip poplar dominated deciduous forest and grassland prairie in the USA. We simulated photosynthetic efficiency and canopy traits, as anticipated from the forthcoming ESA FLEX and CHIME missions and other current and forthcoming airborne and spaceborne hyperspectral missions (e.g., AVIRIS, EnMAP, PRISMA, Tanger, EMIT and DESIS).

Calibration and validation of the FLEX mission require dedicated scaling approaches in space, time, and viewing angles. To achieve this, we propose integrating a tower-based dual-view hyperspectral system with a hyperspectral drone imaging system. We developed an enhanced RotaPrism system that integrates two hyperspectral sensors with a rotating prism module. The QEPro-CUS spectrometer, optimized for far-red SIF retrieval, operates at 730–786 nm with 0.15 nm FWHM resolution, while the HR2000+ES spectrometer captures full VNIR reflectance measurements across 400–900 nm with 0.44 nm FWHM resolution. The system continuously measures incoming irradiance, radiant exitance, and reflected radiance at two-minute intervals, enabling comprehensive and continuous monitoring of SIF emission and surface reflectance dynamics in both directional and hemispheric views.

To capture the spatial variability of hyperspectral reflectance and SIF, we used a mid-spectral-resolution (6 nm) drone-based hyperspectral imaging system covering 400–900 nm (Headwall Nano). To test whether the system could detect SIF, we conducted modeling experiments with SCOPE, a DCMU treatment experiment with strawberry, and disease detection in a rice paddy landscape. We have been operating the enhanced RotaPrism system and conducting regular hyperspectral drone scans at five flux tower sites in South Korea, including rice paddies, deciduous broadleaf forest, evergreen needleleaf forest, wetland, and mixed forest. These datasets will contribute to the calibration and validation of the FLEX mission.

We report several key results, including continuous hyperspectral and SIF data across ecosystems, relationships between SIF and GPP, and comparisons of surface reflectance between Sentinel-2 and hyperspectral drone data.

Effective validation of satellite-derived solar-induced chlorophyll fluorescence (SIF) products from ESA's Fluorescence Explorer (FLEX) mission demands a well-coordinated network of ground-based reference measurements. While SIF provides a direct proxy for photosynthetic activity and represents an essential observable for understanding ecosystem functioning, existing measurement infrastructures remain fragmented, lacking the standardization required for systematic satellite product validation at global scales.

The International Network of Sun-Induced Chlorophyll Fluorescence (INSIF) addresses this gap by establishing a coordinated framework for globally distributed SIF observations. Drawing on experience from existing Fluorescence Box (FloX) instrument deployments and methodologies developed within the ESA DEFLOX project, INSIF creates a sustainable architecture for delivering continuous, traceable SIF measurements across varied ecosystems and climatic zones, encompassing multiple plant functional types.

The network architecture encompasses several fundamental elements. First, measurement standardization is achieved through the deployment of FloX instrumentation equipped with high-specification spectrometers configured for autonomous SIF monitoring. Second, metrological traceability is maintained through portable calibration systems, enabling consistent inter-comparison between distributed measurement sites. Third, standardized data workflows incorporating rigorous uncertainty analysis ensure consistent data quality across the network. Fourth, a unified database infrastructure facilitates community access through open data-sharing policies.

INSIF extends beyond its primary role in FLEX mission support to serve as an integration platform connecting remote sensing and terrestrial ecology communities. The network generates continuous SIF time series complemented by spectral reflectance and vegetation indices, both linked to plant physiology (e.g., photochemical reflectance index), and vegetation biophysical properties (e.g., normalized difference vegetation index), creating datasets that can be directly compared with eddy covariance flux towers, phenological monitoring programs, and additional ecosystem measurements. This multidisciplinary framework strengthens our capacity to investigate ecosystem dynamics by establishing quantitative relationships between photosynthetic efficiency, carbon exchange, and productivity patterns across temporal and spatial dimensions.

Through systematic provision of validation-quality ground measurements, INSIF directly supports FLEX mission science objectives while simultaneously advancing fundamental ecosystem research through enhanced characterization of SIF temporal dynamics and their mechanistic connections to ecosystem processes. This contribution presents the network conceptual design, describes current deployment progress at operational sites, and discusses early findings from pilot locations, highlighting potential synergies for collaborative research and comprehensive ecosystem observation strategies.

In situ-based spectroscopy is an important component of the validation strategy for the upcoming Florescence Explorer (FLEX) satellite mission. Despite careful sensor calibration and the availability of robust retrieval schemes, data products may contain uncertainties that must be quantified and tracked to facilitate data interpretation and use. In situ spectrometer systems with a spectral sampling design comparable to that of FLEX offer comprehensive options for validating mission products, ranging from irradiance and radiance data to surface reflectance and vegetation information such as sun-induced chlorophyll fluorescence (SIF) and other plant-physiological properties. A particularity of the FLEX mission is that the validation approaches should ideally cover gradients of ecosystem representations, including structurally complex forest ecosystems. However, the acquisition of robust validation data in such structurally complex vegetation ecosystems and the interpretation of these data, particularly given their very high spectral and temporal resolution, is highly challenging and requires particular attention.

This contribution summarizes insights and experiences gained from collecting in situ spectroscopy time series across different vegetation types in Switzerland over several years. The data were acquired for FLEX data validation purposes and to advance the understanding of the inherent SIF information content related to subtle ecosystem processes. We first describe our test sites, which include the several Swiss ecosystems (e.g., a mixed temperate forest, an alpine spruce forest, an agricultural site with crop rotation). We then outline the infrastructure used, including the FloX spectrometer systems and the data processing and storage facility. We discuss aspects that complicate the operation, processing, and interpretation of resulting measurement time series. These factors include instrument degradation, intercalibration requirements, canopy heterogeneity, and illumination/shadow effects. We additionally outline strategies to compensate for the related uncertainties in the acquired data.

Our findings can help to optimize the placement of in situ spectrometers in complex forest canopies, to enable intercalibrated sensor networks, and to define strategies that account for shading and other optical effects. All these aspects are critical to facilitate the acquisition of robust and representative in situ validation data in support of FLEX validation activities.