Modelling of forest ecosystem-atmosphere exchange and forest growth patterns with cluster analysis of Eddy covariance flux footprint data from SMEAR Estonia

Eddy covariance measurements are increasingly utilized for assessing the exchange of matter and energy between ecosystems and the atmosphere across various time scales, ranging from hours to years. The flux footprint represents the area observable by flux tower sensors and illustrates how the surface influences the measured flux. Flux footprint models describe both the spatial extent and the specific location of the surface area contributing to the observed turbulent flux. In this study, we utilized a simple two-dimensional parameterization for flux footprint prediction (FFP) developed by Kljun et al. to identify the location of maximum footprint contribution every half hour over six years. These data were then subjected to monthly cluster analysis. Using QGIS, the resulting clusters were overlaid on a base map of the site obtained from the Estonian Land Board, where different compartments have varying growth stages and species composition. The main objective 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. The dataset obtained from the eddy covariance measurement technique was integrated with forestry inventory data, allowing half-hourly data to be selected and visualized using QGIS software.