This research will investigate radiative transfer-based methods to interpret hyperspectral imagery and to estimate leaf biochemical and canopy biophysical variables. These are leaf chlorophyll a+b (Ca+b), dry matter (Cm), water (Cw), leaf area index (LAI), canopy fractional cover, crown volume and tree dimensions. AThese variables are required for modelling land surface / atmosphere interactions, and are indicators of stress and growth. The data will be used to develop and test methofd for estimation by inverse radiative transfer modelling from hyperspectral data in the 400-2500 nm spectral region. In addition, LiDAR data, if available, will provide information regarding the canopy structure that is required for input into the physical models for estimation of canopy biophysical variables. A field sampling campaign in collaboration with IAS, Cordoba, will be conducted for biochemical analysis of leaf chlorophyll content, measuring reflectance and transmittance using a Li-Cor 1800-12. LAI will be measured using a PCA LAI-2000 instrument. Atmospheric measurements will be collected at the time of over-flights for atmospheric correction of images. The research will study i) the simulation of crown and canopy reflectance with the FLIGHT 3-D model; ii) the estimation of crown and canopy structural variables with a LiDAR instrument, if available, such as crown dimensions, tree height and architecture; and iii) validate the link of the PROSPECT leaf model with FLIGHT for estimation of Ca+b and LAI, and canopy fractional cover.