Modeling structural traits of Aleppo pine (Pinus halepensis Mill.) forests with low-density LiDAR

Abstract

ABSTRACT Mediterranean forests of Aleppo pine (Pinus halepensis Mill.) have a crucial role in climate change, as they are extremely adaptive and provide valuable timber or carbon stocks. However, greater detail quantifying those attributes is needed: although National Forest Inventories are acceptable, continuous cover maps are normally lacking. Here, we use the public Spanish low-density LiDAR flights to model above-ground biomass, volume, tree density, basal area and dominant height of naturally regenerated Mediterranean Aleppo pine forests, comparing individual-tree detection and area-based approach. We found R2 and RRMSE among 0.51–0.66 and 40–34% for above-ground biomass, 0.54–0.70 and 34–28% for volume, 0.23–0.45 and 33–28% for tree density, 0.48–0.62 and 32–27% for basal area, and 0.70–0.69 and 11–11% for dominant height. In all cases but dominant height, the area-based approach outperformed the individual-tree detection. Neither time difference between LiDAR flight and ground measurement or past land use affected the area-based approach models, yet the latter had a strong effect on observed productivity. The different definitions of dominant height were equivalent and did not influence the dominant height models. We believe these models, and their corresponding maps, will be a great asset for policymakers and different stakeholders for Aleppo pine forests throughout the Mediterranean basin.