Linking TreeQSM with SAR and ALS to Detect Internal Canopy Allocation Shifts Across Scales

Abstract. Linking remotely sensed forest backscatter with fine-scale tree crown structural dynamics provides insights into tree growth strategies under varying conditions. In this study, we investigate whether branch-scale tree growth allocation dynamics, derived from multi-temporal TreeQSM models, are reflected in SAR and ALS observations. We analyzed branch organization dynamics of silver birch (Betula pendula) using terrestrial laser scanning data from 2021, 2023 and 2025 at a boreal forest site in southern Finland. Branch allocation metrics, including volume-weighted mean diameter (VWMD), small branch fraction (SBF), distal volume fraction, relative branch height, and top canopy volume, were quantified to capture shifts between structural reinforcement and exploratory growth. These metrics were compared with Sentinel-1 SAR features (α, entropy, C11, C22) and ALS-derived canopy metrics (plant area index, vertical complexity index) alongside local structural variables. Results show a consistent trade-off between coarse and fine branching, with strong negative correlations between ΔVWMD and ΔSBF across both periods (ρ = –0.92). SAR-derived α exhibits strong associations with these allocation shifts during 2021–2023 (ρ = –0.81 with ΔVWMD; ρ = 0.75 with ΔSBF), indicating sensitivity to internal redistribution of branch material. ALS metrics from 2021 reflect initial canopy structure and are associated with subsequent allocation shifts. Despite the small magnitude of observed changes, consistent monotonic relationships across datasets suggest that subtle within-crown branch allocation is detectable from satellite and aerial observations, reflecting the surrounding canopy context. However, weakened correlations in 2023–2025 highlight the influence of external factors on SAR signals.