Cluster analysis on Eddy covariance flux footprint data from SMEAR Estonia

Eddy covariance measurements are increasingly used to evaluate the exchange of matter and energy between ecosystems and the atmosphere over different time scales. The flux footprint represents the area detected by flux tower sensors, illustrating how the surface impacts the measured flux. Flux footprint models define both the spatial range and the specific location of the surface contributing to the observed turbulent flux. We applied a simple two-dimensional parameterization for flux footprint prediction (FFP) developed by Kljun et al. to determine the location of maximum footprint contribution every half hour over a six-year period. These data were then analyzed using monthly cluster analysis. The resulting clusters were overlaid on a site base map from the Estonian Land Board in QGIS, where forest area has different compartments with different growth stages and species compositions. The primary goal of this research was to integrate forest inventory data with ecosystem exchange and productivity data continuously recorded by the Eddy Covariance measurement tower at Järvselja, Estonia.