Improving mangrove above-ground biomass estimates using LiDAR

Tree height is a key parameter to accurately quantify above ground biomass (AGB) of trees. Approaches that integrate airborne light detection and ranging (LiDAR) with mapped extents of forests may improve estimation of mangrove heights by providing considerably more measurements of mangrove tree heights than can be achieved using field-based measurements alone. In this study, we present a validated method for quantifying mangrove AGB that was demonstrated for a mangrove forest at Guarás Island, Brazil. The application of LiDAR to estimate mangrove height was confirmed by correlating 89 tree heights measured in the field with LiDAR-derived mangrove heights, resulting in highly robust relationships for Avicennia germinans, Laguncularia racemosa and Rhizophora mangle (R2 = 0.90-0.97, RMSE of 1.24-0.67 m and RMSE% of 11.26%-25.97%). These relationships were used to calibrate a LiDAR-derived canopy height model (CHM) and develop robust relationships between the calibrated-CHM and field-based estimates of AGB (R2 = 0.85-0.92, RMSE of 3.1 kg-42.53 kg, RMSE% of 20.66%-43.81%). This relationship was then applied to the CHM whilst accounting for tree density to estimate mangrove AGB. Total mangrove AGB per hectare was estimated to be 246.90 t ha−1, corresponding closely with previous mangrove AGB measurements within the region. This study found that mangrove height and AGB are statistically related and these relationships can be applied to allometric equations for specific species to improve mangrove AGB estimates. This study demonstrates the capacity for LiDAR-derived tree heights to replace traditional approaches to estimating AGB and improving estimates of mangrove blue carbon storage. Application of LiDAR to determine tree heights will be particularly useful where mangrove is extensive and/or remote