A Comparison of Mobile Laser Scanning Data Acquisition Methods in Closed Forest, Open Woodland and Sub‐Alpine Woodland Ecosystems

Mobile laser scanning (MLS) provides an efficient and accurate method for measuring vegetation structure, increasingly providing new and important information for ecological research and landscape monitoring. However, the effects of varying MLS sampling densities on the characterisation of vegetation structure, particularly across ecosystems differing in structural complexity, remain underexplored. Here, we present the first direct assessment of how structural complexity influences the relationship between MLS sampling density and the derivation of structural metrics. A five‐level sampling framework was applied across open woodland, closed forest and sub‐alpine woodland ecosystems, enabling effects of structural complexity to be determined directly, rather than inferred across independent studies. We found that increasing scanning time by approximately 50%–100% (2–4 min) in 1225 m 2 study plots significantly improved data quality by increasing the diversity of observation angles and achieving a more even distribution of sensor positions within each plot, thereby mitigating occlusion. At the shortest sampling paths, stem detection was reduced by approximately 55%–80% relative to the longest paths, with large proportional reductions observed in all vegetation types. Mean canopy height differences between the shortest and longest paths reached 4.4 m in closed forest stands, compared to ~1–1.7 m in less complex vegetation. Furthermore, voxel occupancy analysis revealed that shorter paths tended to undersample key vegetation layers, such as the upper canopy and understory, while longer paths enabled improved horizontal penetration, particularly where structural complexity was high. Path length densities of approximately 0.18–0.25 m per m 2 of plot area (equivalent to 225–300 m of acquisition path in a 35 × 35 m plot) achieved using a structured gridded trajectory were generally required to obtain reliable estimates of vegetation structure. However, some metrics, particularly ground height, were less sensitive to reduced sampling density in open environments.