ALS Pulse Density Effects on Tree Height Accuracy and the Quality of Elevation and Canopy Rasters

This study investigated the influence of airborne laser scanning (ALS) pulse density on the accuracy of total tree height estimates and the quality of raster products commonly used in individual tree detection (ITD) workflows. Using a high-density (36 pulses per square meter (PPM)) ALS dataset, we generated lower-density subsets and compared derived outputs using a standardized processing pipeline. Tree height estimates were validated against field measurements, and elevation products—digital elevation models (DEMs), digital surface models (DSMs), and canopy height models (CHMs)—were assessed across pulse densities. DSM and CHM quality improved with increasing density, showing reduced bias and tighter variation. In contrast, DEM accuracy remained relatively stable across densities, indicating lower-density ALS may suffice for ground modeling in forested environments. The results also revealed a strong positive relationship between pulse density and total tree height accuracy. Higher-density datasets consistently produced more accurate and less biased tree height estimates, while sparser datasets exhibited systematic underestimation due to missed canopy peaks. These findings emphasize the importance of aligning ALS pulse density with project objectives. While low-density data may be adequate for terrain modeling, higher-density acquisitions are critical for reliable canopy representation and accurate ITD outputs. This study provides operational guidance for forestry practitioners and highlights the value of investing in higher-resolution ALS data for modern forest inventories.