Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurements of height and crown dimensions

Accurate estimates of leaf area index (LAI) could provide useful information to forest managers, but due to difficulties in measurement, leaf area is rarely used in decision-making. A reliable approach to remotely estimating LAI would greatly facilitate its use in forest management. This study investigated the potential for using small-footprint LiDAR, a laser-based remote sensing tool capable of characterizing the vertical structure of forest vegetation, to generate estimates of individual tree leaf area based on LiDAR-derived estimates of tree height and crown dimensions. At a 16-year-old loblolly pine spacing trial in Mississippi, LiDAR-derived estimates of leaf area based on height and crown diameter were on average within 0.1 m2 of ground-based estimates for trees on plots initially planted at a 1.5 m × 1.5 m spacing. For trees on plots originally planted at square spacings of 2.4 m and 3.0 m, LiDAR-based leaf area estimates were below ground-based estimates by 5.8 m2 and 14.5 m2, respectively. At a study site in Texas, LiDAR-derived estimates of leaf area for 4-year-old loblolly pine were, on average, within 0.4 m2 of ground-based estimates. Errors in leaf area estimates were largely due to the inability to generate accurate LiDAR-based estimates of crown dimensions. Tree heights were accurately estimated with LiDAR at both locations, but crown diameter and vertical crown dimensions at the Mississippi site were underestimated on average by 21% and 3%, respectively.