How canopy structure influences LiDAR-derived mangrove biomass estimates and carbon accounting

Mangrove forests are among the most carbon-dense coastal ecosystems, yet estimates of mangrove biomass and carbon stocks derived from remote sensing remain sensitive to methodological choices. In particular, how canopy structure is represented and aggregated from LiDAR data can systematically influence biomass estimates, with direct implications for carbon accounting and climate mitigation assessments. Few studies, however, have directly contrasted individual-crown and area-based biomass pathways within a single LiDAR dataset, leaving it unclear how much of the reported variability in mangrove carbon stocks reflects structural assumptions rather than genuine ecological difference. This study examines the structural sensitivity of LiDAR-derived mangrove biomass estimates by comparing two pathways within a consistent spatial framework: (i) individual-crown above-ground biomass (AGB) estimated from diameter at breast height (DBH) proxies derived from LiDAR-based canopy diameter, and (ii) stand-level AGB estimated from area-based-weighted Lorey’s mean canopy height. High-resolution airborne LiDAR data were acquired over a fringing mangrove system in eastern Java, Indonesia, and used to derive digital surface models, digital terrain models, and canopy height models. The individual-crown-based AGB estimates aggregated to 10 m × 10 m grid cells yielded lower and more constrained biomass values (mean = 153.8 ± 74.7 Mg ha − 1 ; median = 162.73 Mg ha − 1 ), reflecting a tree-level structural perspective. In contrast, the area-based-weighted Lorey’s pathways produced higher biomass estimates at the same spatial scale, with mean AGB values of 167.3 ± 121.7 Mg ha − 1 for the canopy-cover-weighted equation and 183.6 ± 132.5 Mg ha − 1 for the height- weighted equation, representing a mean difference of approximately 10–20% relative to Individual-crown-based estimates. Differences in AGB estimates propagated proportionally into BGB and total ecosystem biomass. Overall, the results indicate that LiDAR-derived mangrove biomass estimates can vary depending on how canopy structure is represented and aggregated, highlighting the need to explicitly document structural assumptions when interpreting LiDAR-based biomass and carbon estimates.