Understanding the Global Climate Change and the way it will affect the Earth and preserving biodiversity are two major challenges of the 21st century. Forests cover 30% of continental surfaces and are a major contributor to the carbon cycle. Sequestration of carbon in forest biomass appears as an important mechanism - in conjunction with reduced emissions - for mitigating climate change. Adequate management of forest resources could strengthen the action of forests as a carbon sink. Forests also play a key role for biodiversity conservation and energy supply. Sustainable management of forest ecosystems is thus critical for the future of mankind. However, the lack of consistent information on forest structure and biomass and on their dynamics at global scale hampers the development of ecological models and of earth-vegetation-atmosphere interaction global models that are essential to improve knowledge on forest ecosystem functioning and to address the challenge of forest sustainable management. By its ability to measure the vertical structure of land cover, airborne Lidar technology is highly qualified for forest applications. NASA's ICESat1 mission (2003-2009) paved the way for Earth observation from space with Lidar systems. ICESat2, launched in September 2018, although primarily designed for ice monitoring will also provide vegetation height measurements worldwide. Vegetation profiles with high vertical resolution should also become soon available with GEDI (NASA) and MOLI (JAXA) missions that will be installed on the ISS at the end of 2018 and in 2019 or 2020, respectively. Although data coverage will be limited from 52°S to 52°N, both these missions will contribute to ecosystem structure observation from space in conjunction with radar missions, especially the BIOMASS ESA's mission. Combined with Sentinel 2 imagery, which provides spectral information with high spatial and temporal resolutions, they will also enable to evaluate the complementarity between information on 3D structure, composition and phenology for a comprehensive monitoring of forest ecosystem conditions. LEAF (Lidar For Earth and Forests) mission has been under study at CNES since 2008 and could contribute in the future to the international effort to sustain global carbon and biodiversity monitoring systems. The system under study combines a NIR full-waveform Lidar profiler and a very high resolution multispectral imager. CNES has supported scientific projects in order to refine instrument specifications and design a system that will meet user requirements. Due to the high cost associated with the development of an airborne prototype, priority has been given to simulation approaches. The aim of this contribution is to present LEAF mission concept and to focus on the recent "LEAF ExpeVal" experiment, designed to consolidate and validate the simulation approaches developed to model a realistic Lidar signal on various forest types, including complex tropical forests. These approaches rely on DART, a radiative transfer model developed at CESBIO. A Lidar module was introduced into DART in the early 2010s and has undergone constant improvement since then. However, simulating a realistic signal also requires to work on model inputs and to develop methods to build detailed forest scenes. The objective of the LEAF-Expeval experiment was twofold: first, to validate the simulations by comparing simulated and experimental Lidar waveforms on a tropical forest; second, to develop a new approach to simulate spaceborne Lidar data from small footprint airborne Lidar data (ALS data). Achieving the first objective is a key step to refine LEAF system specifications in order to ensure that the system will provide accurate height measurements and vegetation profiles on tropical forests, which are the most constraining environment for a space Lidar. Field and airborne data were collected in Paracou experimental forest in French Guiana. The processing and analysis steps include (1) the construction of forest scenes from TLS (Terrestrial Lidar Scanner) and reflectance measurements on a dense forest plot, (2) the estimation of the calibration coefficient of the airborne system, coefficient that is used to convert digital count into physical units, (3) the simulation of airborne Lidar data on the forest scene using DART and (4) the comparison of simulated and real waveforms. As ALS data are now widely available, achieving the second objective would enable the simulation and evaluation of LEAF data on a variety of forest ecosystems. This part of the study relies on Lidar simulations realized on temperate broadleaved forest scenes created using Allostand (Amap) and Genesis software. Small footprint lidar point clouds were simulated using DART and were in turn used to simulate large footprint lidar waveforms. The resulting waveforms were compared to reference data, i.e. large footprint waveforms obtained directly with DART on the same forest scenes. First results are encouraging and showed that large footprint waveforms obtained from the processing of small footprint data were very similar to reference waveforms, even with a change of waveband between lidar point clouds and large footprint waveform.