Mediterranean forests are characterized by heterogeneous vegetation structure and dense shrub layers that strongly influence fuel continuity, ecosystem functioning, and forest management. However, shrub biomass estimation remains difficult to characterize consistently using remote sensing and field data given that canopy screening, vegetation heterogeneity, and acquisition geometry can influence the representation of near-ground structure. Airborne laser scanning (ALS), terrestrial laser scanning (TLS), and handheld/mobile laser scanning (HMLS) provide different perspectives on forest structure, although structural metrics derived from these platforms are not inherently comparable across varying canopy conditions. While previous studies have evaluated combinations of airborne and terrestrial LiDAR systems for forest inventory and understory biomass, direct comparisons of ALS, TLS, and HMLS within the same Mediterranean forest plots remain limited, particularly for shrub structural metrics commonly used in biomass and fuel characterization.

This study evaluates countrywide ALS coverage of 2024 together with TLS and HMLS observations acquired in 30 circular plots located in Monsanto Forest Park, Lisbon, Portugal, during winter 2025 to compare how different LiDAR acquisition perspectives represent understory vegetation structure under Mediterranean forest conditions. Field observations of shrub height and species presence were collected at regular intervals using transect-based sampling methods and combined with harmonized multi-platform LiDAR acquisitions to support cross-platform comparison of understory structural representation. LiDAR-derived shrub metrics were extracted from height-normalized point clouds after filtering the understory layer between 0.2 and 3.0 m. The comparison focused on shrub height (SH), shrub cover (SC), and shrub biomass density (SBD). Metrics were derived using a voxel-based approach with a voxel size of 0.5 m applied consistently across ALS, TLS, and HMLS datasets. The SH was estimated as the mean height of occupied shrub-layer voxels, while SC was estimated from the proportion of occupied horizontal voxel cells within each plot. Shrub biomass density (SBD) was subsequently estimated from shrub height and shrub cover using an pre-existing equation empirical that combines vertical and horizontal shrub structure.

The study provides a basis for interpreting differences in SH, SC, and SBD estimates obtained from airborne, terrestrial, and mobile LiDAR observations in Mediterranean forests. Understanding the comparability of these metrics is important for determining whether shrub structural metrics from different LiDAR platforms can be interpreted consistently. The study is also a step forward for understanding the potential and limitations in the use of these technologies to estimate understory biomass vegetation.