Monitoring the structure of forest restoration plantations with a drone-lidar system

Abstract

We are in an unprecedented moment for promoting forest restoration globally, with international and regional pledges to restore at least 350 million hectares by 2030. To achieve these ambitious goals, it is necessary to go beyond traditional plot-scale assessments and develop cost-effective technologies that can monitor the structure and function of restored forests at much broader scales. Lidar remote sensing in unmanned aerial vehicle (UAV) platforms can be an agile and autonomous method for monitoring forest restoration projects, especially under conditions when information updates are frequently needed in relatively small areas or, when using an airplane-borne lidar system may be not financially viable. Here, we explored the potential of an UAV-borne lidar system to assess the outcomes of a mixed-species restoration plantation experiment, designed to maximize aboveground biomass (AGB) accumulation. The experiment was established in Brazil's Atlantic Forest, with 20 native tree species, by combining two levels of planting density and two management levels, totaling four treatment combinations and one control (plots left over for natural regeneration). We analyzed three structural variables from lidar data (canopy height, gap fraction and leaf area index) and one from field inventory data (AGB). Structural differences between the treatments and the control plots were reliably distinguished by the UAV-borne lidar system. AGB was strongly correlated with canopy height, allowing us to elaborate a predictive equation to use the UAV-borne lidar system for monitoring structural features in other restoration plantations in the region. UAV-borne lidar systems showed enormous potential for monitoring relatively broad-scale (thou-sands of hectares) forest restoration projects, providing an important tool to aid decision making and accountability in forest landscape restoration.