Canopy layers form essential structural components, affecting stand productivity and wildlife habitats. Airborne laser scanning (ALS) provides horizontal and vertical information on canopy structure simultaneously. Existing approaches to assess canopy layering often require prior information about stand characteristics or rely on pre-defined height thresholds. We developed a multi-scale method using ALS data with point densities >10 pts/m² to determine the number and vertical extent of canopy layers (canopy_layer, canopy_length), seasonal variations in the topmost canopy layer (canopy_type), as well as small-scale heterogeneities in the canopy (canopy_{heterogeneity}). We first tested and developed the method on a small forest patch (800 ha) and afterwards tested transferability and robustness of the method on a larger patch (180,000 ha). We validated the approach using an extensive set of ground data, achieving overall accuracies >77% for canopy_type and canopy_{heterogeneity}, and >62% for canopy_layer and canopy_length. We conclude that our method provides a robust characterization of canopy layering supporting automated canopy structure monitoring. Full article