Estimating Extreme Gusts via Optical Flow Tracking from Defoliated Tree Motion

Sai Kulkarni , John Hillier, Tim Marjoribanks , Sarah Bugby, Daniel Bannister, Jonny Higham, Rufus Dickinson, Matthew Baddock

Peak 3-second gusts (s₃) during severe storms are critical drivers of wind damage, yet their fine-scale dynamics remain difficult to measure. Visual Anemometry (VA) unlocks the possibility of spatially dense wind speed estimates, yet its performance under extreme winds remains poorly understood. Here, we combine physics-based simulations of tree motion with Optical Flow Tracking Velocimetry (OFTV), allowing a first assessment of s₃ estimation for winds of 25-144 km/h across camera angles of 0-180°. Modelled tree velocities increased approximately linearly with input wind speed and were captured well by OFTV (R² ≈ 0.9, p < 0.05), mechanistically demonstrating the validity of VA for extreme winds and structural loading. Against expectations, both predictive performance and the relationship between video motions and estimated s₃ are not significantly affected by camera angle (0°-180°), importantly indicating that multi-branch tree motion produces an angularly isotropic response. Moreover, directional effects reduce, becoming negligible, under strong winds. Demonstrating the robustness of tree-based VA for extreme wind gusts (e.g. no direction-dependent calibration needed) is a foundational step towards enhanced gust detection, hazard mapping, and risk assessment for planning and insurance.