Drones and machine learning for estimating forest carbon storage

Abstract

Abstract Estimating forest carbon storage is crucial for understanding sink capacities to facilitate carbon crediting and mitigate climate change. Images captured with RGB or LiDAR cameras, mounted on drones, could be used to derive forest structural parameters such as canopy area, height, and tree diameter. Further, these data could be used in Machine Learning models and allometric equations to rapidly and precisely estimate and model carbon storage in their living biomass. Graphical Abstract