Estimating tree volume based on crown mapping by UAV pictures in the Amazon Forest

Abstract

The use of remote sensing images obtained by unmanned aerial vehicle (UAV) systems enables measuring the morphometry of the tree canopy to estimate the volume stock in the Amazon Forest. In this study, we used RGB images from a low-cost UAV to map tree species and extract volumetric stock estimates in an Amazonian Forest. Individual tree crowns (ITC) were outlined in the UAV images and identified to the species level using forest inventory data. The average diameter and crown area of the trees were measured to estimate the volume, basal area and DBH per diameter class for 260 ha of tropical forest. The RMSE volume adjustment for the separate field inventory dataset was 19.31% with an R2 of 0.967. The UAV system images has the potential to map tree species and estimate tree biometry in the Amazon Forest, providing valuable insights for forest management and conservation.