What Is the Most Suitable Height Range of ALS Point Cloud and LiDAR Metric for Understorey Analysis? A Study Case in a Mixed Deciduous Forest, Pokupsko Basin, Croatia

Understorey evaluation is essential in wildlife habitat management, biomass storage and wildfire suppression, among other areas. The lack of a standardised methodology the field measurements, their subsequent analysis, forces researchers to look for procedures that effectively extract understorey data make management decisions corresponding actual stand conditions. In this sense, when analysing characteristics from LiDAR data, it very usual ask: “what value should we set height range to?” It also answer by setting numeric on basis previous research. Against background, research aims identify optimal canopy base (HCB) filter–LiDAR metric relationship estimating (UH) cover (UC) using Pokupsko Basin lowland forest complex (Croatia). First, several HCB values per plot were obtained (measured HCBi—HCBM-i, where i ϵ (minimum, maximum, mean, percentiles)), then they modelled based metrics (estimated HCBi—HCBE-i). These thresholds, measured estimated HCBi plot, used as point cloud filters estimate parameters directly located under layer. way, was possible predict UH with errors (RMSE) between 0.90 2.50 m UC 8.8 18.6 percentage. Finally, sensitivity analysis showed filter (the upper threshold select points) most important factor affecting estimates, while are factors estimates.