The TRuStEE network of excellence designed a research programme with 12 multidisciplinary and intersectoral individual research projects that span 4 key areas and the relative work packages (WP).
In WP1, the link between the essential biodiversity variables categories (EVBs), the ecosystem functional properties (EFPs) and the vegetation optical properties was analysed using complete datasets of remote sensing information acquired and processed at different spatial, spectral and temporal resolutions. Complementary, a deep study on innovative instruments and data chain processing was performed. An innovative spectrometer for vegetation optical property acquisition was made operative and deployed on a flux tower. Robust techniques for intelligent data capture from UAVs were also developed to ensure good quality data acquisition. An operational data chain processing for UAV images was finally developed.
In WP2, the link between vegetation fluorescence, hyperspectral optical indices and vegetation functioning was investigated on different terrestrial ecosystems in order to verify the possibility to use optical indices related to photosynthesis in ecosystem models.
A first dataset of coupled active and passive F measurements was obtained using a newly automated platform. The data were collected over a Free-air CO2 enrichment experiment in Germany. Furthermore, the anisotropic properties of F and reflectance at different wavelengths were empirically characterised using high resolution radiance data collected over different canopy types with a mobile goniometer capable of collecting data at different view angles.
Time series of fluorescence and vegetation optical indices obtained with unattended high resolution field spectrometers, were also analysed in order to decouple the low and fast temporal dynamics and to link them to plant traits and ecosystem functional properties.
In WP3, the expertise and new understanding of vegetation systems emerging from WP1 and WP2 were transferred in real case studies in different. EFPs and plant traits (PTs) maps were derived from both ground and remote sensing data in target areas where plant variation was induced by different factors. For example, seasonal changes in canopy evapotranspiration were estimated in a tree-grass ecosystem using an energy balance model. Canopy structure was estimated with Structure from Motion techniques applied to data collected from UAV. Maps of early stress conditions were obtained through spectral indices and fluorescence.
In WP4, a review of the methods and techniques for the upscaling of important variables concerning vegetation and the environment was made. A suite of statistical data-driven and machine learning techniques was developed to up-scale PTs and EFPs from in-situ data at different spatial scales using remote sensing data . An open source package to derive at global scale EFPs using eddy covariance observations was developed using spectral information retrieved from Sentinel-2 with machine learning techniques. The uncertainties of the globally produced maps were also evaluated.
TRUSTEE scientific results were disseminated in scientific open access papers. Reports are available and exploitable on the TRUSTEE website with the link to repository of open source code created for the data processing. The datasets collected remotely with different sensors and platforms were organized in a WebGIS and are now open and accessible to public. In particular, a handbook of exercises linked to this dataset was prepared and published on the project website to enhance the data exploitability. These exercises were organized as a tutorial for undergraduate and master students interested in remote sensing application for ecosystem modelling.
