Estimating tree biomass using UAV Lidar in Braila Islands LTSER site

Forest biomass provides a valuable metric for assessing both ecosystem productivity and carbon storage capabilities. Unmanned aerial vehicle (UAV) equipped with Light Detection and Ranging (LiDAR) technology, represents a powerful tool for estimating tree biomass due to its capacity to produce high-resolution three-dimensional data. We tested a methodology for estimating tree biomass within an area located in the flood plain of the Danube River, part of Brăila Islands Long-Term Socio-Ecological Research (LTSER) site. This area is characterized by floodplain forest plantations and natural wetlands under semi-natural hydrological regime. We selected six forest plots, representative for the area in terms of species composition and age structure. The forest composition is mainly based on willow ( Salix sp. ), poplar ( Populus sp. ) and ash ( Fraxinus sp ) species, planted in relation with the flooding regime. On the ground, diameter at breast height (DBH), and total tree height for 80 individual trees were recorded in order to estimate their biomass using species-specific allometric equations. These estimations are further used for LIDAR based model calibration. We have conducted a LiDAR survey over the sampling area of approx. 22 Ha, collecting a high-density point cloud to capture forest structure. The LiDAR dataset is used to generate a Digital Terrain Model (DTM) and a Canopy Height Model (CHM), as well as to derive forest and tree specific indicators (i.e. density, number of stems, heights). Preliminary results indicate that canopy height and LiDAR-derived metrics exhibit good correlations with field-based biomass estimates. Additionally, integrating LiDAR-derived, forest structure with environmental covariates, such as soil moisture and topographic features, improves biomass estimation accuracy. The study highlights the potential of UAV LiDAR, for biomass assessment in floodplain forests, in order to improve traditional field-based inventory methods that are challengingdue to seasonal flooding and dense vegetation and accessibility. The findings have implications for carbon stock assessments, ecosystem monitoring, and sustainable management strategies within the Brăila Islands LTSER site.