A rapid approach for integrating high-resolution remote sensing and eddy flux observations

The Eddy Covariance (EC) method is a state-of-the-art ecosystem flux measurement technique. EC data is used to calibrate and validate biogeochemical models for downstream Earth Observation (EO) products. Despite being a point measurement, the EC method samples an area around the measurement tower, called a flux footprint (FFP). The extent and direction of an FFP depend on the wind speed and direction and the state of the atmosphere, thus it changes continuously. Although most of the EC towers are placed in homogeneous areas, where the footprint direction should not play a role, at the modern 10-m spatial resolution of EO satellites such as Sentinel-2, the area under FFP may be seen as heterogeneous because of phenological differences or temporal changes in vegetation cover. The land cover heterogeneity under the FFP may cause challenges in interpreting the EC data and discrepancies in the calibration and validation of EO downstream products.

In this study, we investigated the FFP heterogeneity of 72 European EC sites from the ICOS Warm Winter 2020 dataset (https://doi.org/10.18160/2G60-ZHAK). Firstly, the footprint size was statistically estimated according to the dominant plant functional type. Secondly, the heterogeneity was assessed for a circular buffer and twelve sub-sectors of the buffer on Sentinel-2-derived normalised difference vegetation index (NDVI) with several statistical criteria (e.g. Tukey’s test, Z-score). This approach was demonstrated to be an alternative to precise FFP models, as the latter might require parameters not available to the end users, such as standard deviation of the v-wind component or atmospheric boundary layer height. The tool was developed as a stand-alone application and can be used for spatial heterogeneity assessment beyond the tested EC footprints.