An Evaluation of the Effects of UAS Flight Parameters on Digital Aerial Photogrammetry Processing and Dense-Cloud Production Quality in a Scots Pine Forest

The application of unmanned aerial systems (UAS) in forest research includes a wide range equipment, systems, and flight settings, creating need for enhancing data acquisition efficiency quality. Thus, we assessed the effects flying altitude lateral longitudinal overlaps on digital photogrammetry (DAP) processing ability its products to provide point clouds forestry inventory. For this, used 18 combinations settings acquisition, nationwide airborne laser scanning (ALS) dataset as reference data. Linear regression was applied modeling DAP quality indicators model fitting function settings; equivalence tests compared DAP- ALS-products. Most DAP-Digital Terrain Models (DTM) showed moderate high agreement (R2 > 0.70) when fitted ALS-based models; nine models had slope within 1% region equivalence. best DAP-Canopy Height Model (CHM) generated using ALS-DTM with an R2 = 0.42 ALS-CHM, indicating reduced similarity. Altogether, our results suggest that optimal combination should include 90% overlap, 70% minimum 120 m above ground level, independent availability ALS-derived DTM height normalization. We also provided insights into outputs future applications similar stands, emphasizing benefits comprehensive scene reconstruction canopy surface detection.