Mediterranean-type ecosystems are among the most affected by global climate change due to an increase in droughts and fires. Sentinel-2 satellites are currently among the best alternative for operational vegetation properties monitoring because of their temporal revisit and global coverage. The increasing availability of spaceborne imaging spectrometer (e.g. DESIS, PRISMA, EnMAP) and the preparation of missions ensuring global accessibility (e.g. CHIME, BIODIVERSITY) will enable the estimation of vegetation traits with better accuracies. The SENTHYMED project aims to study the complementarity between multi- and hyperspectral images to evaluate Mediterranean forest functional traits. The objective is to estimate canopy pigment, leaf water and dry matter contents from physical model inversion using DART radiative transfer model. A preliminary step is to study the influence of DART optical properties parametrization on remote sensing image simulation in order to simulate scenes as accurately as possible. Two forests in the South of France, mainly composed of evergreen oaks and pubescent oaks, with heterogeneous canopy structure, were studied. UAV LiDAR data were first acquired and converted into voxel matrices of plant area density values with AMAPVox. Pytools4dart was then used to build the mock-ups, handle DART parameterization and generate images in spectral reflectance unit at canopy level. Several simulations were implemented, assigning different optical properties to the underground and to the canopy. These images were compared to airborne AVIRIS-Next generation acquisitions, acquired close to the field campaign that took place in June 2021 and where in-situ measurements were collected for calibration and validation of DART simulations.