Remote sensing can provide systematic global estimations of vegetation structure and biochemistry imparting data such as leaf area index (LAI), water content or fractional light interception by green vegetation (fPAR). However a global network of standardize validation sites is required to reduce the uncertainty of these products. As part of that effort, SpecNet (Spectral Network), an independent international collaborative research iniciative, promotes the acquisition of field optical remote sensing and vegetation properties. These sites are also generally part of the flux tower network (FLUXNET) to better understand carbon and water vapor fluxes. The proposed Staff Exchanges will promote SpecNet by linking joint research activities that will work to develop methodologies to estimate vegetation biochemistry and structure from remote sensing, including the design, validation and assessment of new bi-dimensional and tri-dimensional radiative transfer models. We will emphasize the analysis and quantification of the uncertainty associated with the estimation of the vegetation parameters at different spatial scales, linking them to the flux tower measurements. A scaling-up methodology will be tested by comparing spectral information at leaf, canopy and ecosystem level using laboratory and field spectroscopy, airborne hyperspectral image, Lidar data and multispectral satellite data. We will adapt and distribute standard field protocols for different ecosystems and establish consensus on the metadata to include in the datasets. The results of these contributions will be made available to the academic community, and research conclusions drawn will be published in international journals. In these Staff Exchanges each participant will also seek to share their knowledge within their area of expertise by organizing training seminars for undergraduate and graduate students, also involving local, regional and/or national management agencies according to their needs or demands.