In tropical forests, ecological processes heavily depend on the structure of the canopy (size, shape, dominance of trees) and also the ability of each species to capture light and nutrients in the soil. Airborne HR imaging spectroscopy has demonstrated its potential in tropical environments: Confirmation that trees structure combined with leaf biochemical properties influence the radiometric signal reflected by vegetation and contribute to the estimation of biodiversity; Identification of tree species; Mapping at fine scales as well local species diversity and changes in forest species communities. But what performance and limits for spaceborne system ? This presentation highlight the consolidation work made to prepare the HYPXIM Satellite Mission that aims to provide information about the characteristics of the vegetation from local scale (crowns) to regional scale (species communities across landscapes). HYPXIM will provide estimates of vegetation properties with sufficient precision to force the model variables or data assimilation procedures.... The accelerating loss of biodiversity is a major environmental trend. Tropical ecosystems are particularly threatened due to climate change, invasive species, farming and natural resources exploitation. Recent advances in remote sensing of biodiversity confirmed the potential of high spatial resolution spectroscopic imagery for species identification and biodiversity mapping. Such information bridges the scale-gap between small-scale, highly detailed field studies and large-scale, low-resolution satellite observations. In order to produce fine-scale resolution maps of canopy alpha-diversity and beta-diversity of the Peruvian Amazonian forest, we designed, applied and validated a method based on spectral variation hypothesis to CAO AToMS (Carnegie Airborne Observatory Airborne Taxonomic Mapping System) images, acquired from 2011 to 2013. There is a need to understand on a quantitative basis the physical processes leading to this spectral variability. This spectral variability mainly depends on canopy chemistry, structure, and sensor’s characteristics. 3D radiative transfer modeling provides a powerful framework for the study of the relative influence of each of these factors in dense and complex canopies. We simulated series of spectroscopic images with the 3D radiative model DART, with variability gradients in terms of leaf chemistry, individual tree structure, spatial and spectral resolution, and applied methods for biodiversity mapping. This sensitivity study allowed us to determine the relative influence of these factors on the radiometric signal acquired by different types of sensors. Such study is particularly important to define the domain of validity of our approach, to refine requirements for the instrumental specifications, and to help preparing hyperspectral spatial missions to be launched at the horizon 2015-2025 (EnMAP, PRISMA, HISUI, SHALOM, HYSPIRI, HYPXIM). Simulations in preparation include topographic variations in order to estimate the robustness of image processing methods for mountainous ecosystems.