This study aimed to understand which vegetation indices (VIs) are an ideal proxy for describing phenology and interannual variability of Gross Primary Productivity (GPP) in short-rotation coppice (SRC) plantations. Canopy structure- and chlorophyll-sensitive VIs derived from Sentinel-2 images were used to estimate the start and end of the growing season (SOS and EOS, respectively) during the period 2016–2018, for an SRC poplar (Populus spp.) plantation in Lochristi (Belgium). Three different filtering methods (Savitzky–Golay (SavGol), polynomial (Polyfit) and Harmonic Analysis of Time Series (HANTS)) and five SOS- and EOS threshold methods (first derivative function, 10% and 20% percentages and 10% and 20% percentiles) were applied to identify the optimal methods for the determination of phenophases. Our results showed that the MEdium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) had the best fit with GPP phenology, as derived from eddy covariance measurements, in identifying SOS- and EOS-dates. For SOS, the performance was only slightly better than for several other indices, whereas for EOS, MTCI performed markedly better. The relationship between SOS/EOS derived from GPP and VIs varied interannually. MTCI described best the seasonal pattern of the SRC plantation’s GPP (R² = 0.52 when combining all three years). However, during the extreme dry year 2018, the Chlorophyll Red Edge Index performed slightly better in reproducing growing season GPP variability than MTCI (R² = 0.59; R² = 0.49, respectively). Regarding smoothing functions, Polyfit and HANTS methods showed the best (and very similar) performances. We further found that defining SOS as the date at which the 10% or 20% percentile occurred, yielded the best agreement between the VIs and the GPP; while for EOS the dates of the 10% percentile threshold came out as the best.

Surface albedo is a fundamental radiative parameter as it controls the Earth’s energy budget and directly affects the Earth’s climate. Satellite observations have long been used to capture the temporal and spatial variations of surface albedo because of their continuous global coverage. However, space-based albedo products are often affected by errors in the atmospheric correction, multi-angular bi-directional reflectance distribution function (BRDF) modelling, as well as spectral conversions. To validate space-based albedo products, an in situ tower albedometer is often used to provide continuous “ground truth” measurements of surface albedo over an extended area. Since space-based albedo and tower-measured albedo are produced at different spatial scales, they can be directly compared only for specific homogeneous land surfaces. However, most land surfaces are inherently heterogeneous with surface properties that vary over a wide range of spatial scales. In this work, tower-measured albedo products, including both directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), are upscaled to coarse satellite spatial resolutions using a new method. This strategy uses high-resolution satellite derived surface albedos to fill the gaps between the albedometer’s field-of-view (FoV) and coarse satellite scales. The high-resolution surface albedo is generated from a combination of surface reflectance retrieved from high-resolution Earth Observation (HR-EO) data and moderate resolution imaging spectroradiometer (MODIS) BRDF climatology over a larger area. We implemented a recently developed atmospheric correction method, the Sensor Invariant Atmospheric Correction (SIAC), to retrieve surface reflectance from HR-EO (e.g., Sentinel-2 and Landsat-8) top-of-atmosphere (TOA) reflectance measurements. This SIAC processing provides an estimated uncertainty for the retrieved surface spectral reflectance at the HR-EO pixel level and shows excellent agreement with the standard Landsat 8 Surface Reflectance Code (LaSRC) in retrieving Landsat-8 surface reflectance. Atmospheric correction of Sentinel-2 data is vastly improved by SIAC when compared against the use of in situ AErosol RObotic NETwork (AERONET) data. Based on this, we can trace the uncertainty of tower-measured albedo during its propagation through high-resolution EO measurements up to coarse satellite scales. These upscaled albedo products can then be compared with space-based albedo products over heterogeneous land surfaces. In this study, both tower-measured albedo and upscaled albedo products are examined at Ground Based Observation for Validation (GbOV) stations (https://land.copernicus.eu/global/gbov/), and used to compare with satellite observations, including Copernicus Global Land Service (CGLS) based on ProbaV and VEGETATION 2 data, MODIS and multi-angle imaging spectroradiometer (MISR).

A semi-empirical method for estimating actual evapotranspiration (ETa) based on ancillary and NDVI data, named NDVI-Cws, is currently being refined for improved applicability to wetlands. The investigation, in particular, addresses the case of semi-natural ecosystems where the impact of meteorological water stress (WS) is limited by groundwater resources. To adapt to this situation, the application of the NDVI-Cws method is preceded by a calibration phase based on spatially enhanced Land Surface Analysis Satellite Application Facility (LSA SAF) evapotranspiration products. This calibration is currently performed in the main wetlands of Tuscany (Central Italy) identified in the Ramsar Convention. The calibrated NDVI-Cws version is then applied to all regional Ramsar areas, yielding outputs that are first examined all over Tuscany. Next, the model estimates are quantitatively assessed versus ETa observations taken in a forest and a grassland Ramsar site. The results of these independent tests show the improvement achieved by the calibration phase with respect to the original model version. This supports the potential of the refined NDVI-Cws method to yield reasonably accurate daily ETa estimates for wetlands at a spatial resolution that is mainly dependent on the NDVI data used.

The uncertainty evaluation of eddy covariance flux measurements has been thoroughly developed in the last two decades. However, the various methods proposed are not yet fully compliant with the internationally accepted metrological guidelines, e.g. those indicated in the Guide to expression of uncertainty in measurement and related supplements issued by the Joint Committee for Guides in Metrology and internationally adopted as reference in metrology. Scope of this presentation is to implement the formal methodology for the determination of a combined standard uncertainty for the estimated fluxes through the law of propagation of uncertainty, assuming independent variables. Compared to previous methods, this approach considers the complete flux equation, including the coordinate rotations and the physical conversions and, most importantly, provides an easy to implement analytical tool to quantify the individual contributions to the full measurement uncertainty arising from all the variables actually included in the calculation (turbulent wind components, scalar of interest, air temperature and pressure). The linear method adopted for uncertainty propagation has been also validated through a Monte Carlo simulation, which is the gold standard for propagating probability distributions. The methodology has been applied to a full year of carbon dioxide fluxes measured in the San Rossore 2 ICOS Ecosystem Station, a Mediterranean forest, but it is valid for most of the common eddy covariance systems, being based on theoretical principles. The median of the estimated relative uncertainty of the flux over the considered year is 13.5%, assuming an instrumental uncertainty of 30 Pa for the barometer, 0.5 °C for the thermometer, 4 ppm for the CO2 analyzer and 0.4 m/s for the three components of the sonic anemometer. The main uncertainty contributions come from the analyzer and the vertical component of the anemometer, with medians of the evaluated relative uncertainties equal to 11.9% and 3.25%, respectively. Preliminary results suggest that the method is robust and confirm expectations about the relative contribution of the different instruments used for flux determination, but at the same time constitute a tool for a sounder metrological assessment of all eddy covariance measurements and applications.