Strengths and limitations of assessing forest density and spatial configuration with aerial LiDAR

Changes in the structural state of forests of the semi-arid U.S.A., such as an increase in tree density, are widely believed to be leading to an ecological crisis, but accurate methods of quantifying forest density and configuration are lacking at landscape scales. An individual tree canopy (ITC) method based on aerial LiDAR has been developed to assess forest structure by estimating the density and spatial configuration of trees in four different height classes. The method has been tested against field measured forest inventory data from two geographically distinct forests with independent LiDAR acquisitions. The results show two distinct patterns: accurate, unbiased density estimates for trees taller than 20 m, and underestimation of density in trees less than 20 m tall. The underestimation of smaller trees is suggested to be a limitation of LiDAR remote sensing. Ecological applications of the method are demonstrated through landscape metrics analysis of density and configuration rasters.

Research highlights
► A new model predicts tall tree density with precision.
► Short tree density is underpredicted.
► Underprediction of short trees is a limitation of aerial LiDAR.
► Ecological applications of assessing tree density and configuration are demonstrated.