Remote sensors, both onboard orbital and aircraft platforms or unmanned aerial vehicles (UAVs), are essential for the effective monitoring of forested landscapes. Particularly, UAV systems can generate high-resolution images that provide accurate information on forest stands with or without the need for ground-based data (e.g., calibration or validation) to estimate important forest attributes such as the number of trees, aboveground biomass, or canopy openness (Almeida et al. 2020a, Kotivuori et al. 2020; Ferreira et al. 2020). The development and understanding of the potential of UAV-borne remote sensors are essential for the effective monitoring of forested landscapes in large areas and will play an important role during the UN Decade of Ecosystem Restoration. Here, we explored the use of a UA-borne lidar and hyperspectral (HSI) system to assess the outcomes of a mixed-species restoration plantation experiment designed in a species richness gradient in southeastern Brazil. We used a UAV-lidar-Hyperspectral system to quantify forest structure variables (from lidar) and vegetation indexes (from HSI) and associated these variables with AGB stocks measured in the field and the species richness plantation.