Use of low point density ALS data to estimate stand-level structural variables in Mediterranean Aleppo pine forest

Abstract

Little research has focussed on the use of low point density airborne laser scanning (ALS) technology in Mediterranean Aleppo pine (Pinus halepensis Mill.) forest to derive key stand characteristics for forestry. The objective of this research was to develop models of Aleppo pine structural variables from ALS point clouds with a point density of 1 point m⁻² and field information, in an area located in north-eastern Spain. Field stand metrics were obtained within 45 plots, 30 m in diameter. A multiple regression analysis was performed in order to develop the models for mean height, squared mean diameter, basal area, timber volume, stand density and crown ratio, which led to the following R² values: 0.87, 0.84, 0.89, 0.89, 0.48 and 0.69, respectively. ALS-derived metrics included in the models were maximum height, the 99th, 95th and 50th canopy height percentiles, the skewness, the kurtosis, the standard deviation, the coefficient of variation and the percentages of all and first returns from above 1 m of the ground surface. With the exception of stand density, the final models are appropriate to be used in forest management operations in Mediterranean Aleppo pine forest. This study demonstrates the usefulness of low point density ALS data to accurately estimate key structural parameters of Aleppo pine forest using an area-based approach.