The AMAZECO project is about helping governments to make use of LIDAR data for their conservation and sustainable development purposes, and at the same time doing it in a globally harmonized manner, so that all information can also be useful toward monitoring UN 2030 Global Sustainable Goals. We aim to transform the sheer amount of data available through LIDAR surveys into simple information describing ecosystems that can be meaningful and easy to conceptualize by decision and policy-makers. Global information sources may typically be of little help to national governments, because they neglect the specific circumstances of each region. We follow a different approach: our vision is one of a crowdsourced global product fed from local efforts, by creating the tools to facilitate local stakeholders to use these data for their own conservation and sustainable development purposes, empowering local action while enabling a globally-harmonized product. We concentrated in ecosystem vertical profiles (EVPs), which characterize the vertical distribution of sessile biological entities in an ecosystem. In Valbuena et al. (2020) we advocated for a standardization of ecosystem morphological traits – vegetation height, cover, and structural complexity – derived from EVPs characterized by LIDAR. These traits should focus on being relevant to the ecosystem, and not on the means for measuring them. Thus, the objective of the research was in demonstrating that we can deliver platform-independent EVP traits from both satellite and airborne LIDAR sensors and provide the means for a global ecosystem structure LIDAR product that can be crowdsourced through national Biodiversity Observation Networks (BONs). This was enabled by high performance computing (HPC) workflows for common satellite and airborne LIDAR derivation of ecosystem traits, producing and implementing a first prototype product covering the whole of the Brazilian Amazon region with traits produced from combined satellite and airborne LIDAR. The satellite LIDAR was obtained from the currently operational global ecosystem dynamics investigation (GEDI) mission. The airborne LIDAR workflow made use of the extensive dataset of transects from the ‘improving biomass estimation methods for the Amazon’ (EBA), plus data from the Sustainable Landscapes Brazil (SLB) project. The product consisted of a multilayered raster data product with LIDAR measures of EVP traits, including estimations of their uncertainties and a demonstration of how airborne LIDAR can be used to improve those over a satellite product. The code developed has procedures incorporated in the rGEDI package (Silva et al. 2020), and HPC pipelines to enable replication through