Deep learning methods such as Mask R‑CNN enable the precise delineation of single-tree crowns from remote sensing data. However, their segmentation performance still depends on local stand conditions. Using UAV multispectral imagery and lidar canopy height models (CHM), we assessed the influence of tree species composition, stand density, and foliage condition on the robustness of deep-learning-based single-tree segmentation....