Seeing Gusty Winds: Optical Tracking of Tree Motion Captures Peak 3‐s Gust Velocities

ABSTRACT Peak 3‐s gust speed () is a key meteorological metric for potentially impactful winds. It is widely used in meteorology and engineering, but traditional anemometry is limited by sparse measurements. This proof‐of‐concept study is the first to relate Optical Flow Tracking Velocimetry (OFTV) derived wind estimates explicitly to , by capturing fine‐scale wind variability from video footage of trees. While calibration is required, this approach is simple, transparent and avoids the descriptor‐based Beaufort scale. So, it is a potential improvement or a component of frameworks that use machine learning or physics‐based structural approaches. Results from a pear tree in a domestic setting show correlations between OFTV‐ and cup‐anemometer data ( R 2 = 0.65, p < 0.05), confirming that can be extracted using only OFTV. Interestingly, OFTV‐ are consistent and strongly correlated ( R 2 ≥ 0.92) across a range of reference objects (i.e., a flag, parts of the tree crown, grass). This insight suggests that identifying specific objects is unnecessary in simple scenes, potentially simplifying future crowd‐sourced visual anemometry, although it may still be required in cluttered urban environments. Furthermore, occur across objects within ±1–5 s of each other, indicating a robustness of measurement. Collectively, these insights are a valuable step towards improved wind distribution mapping (e.g., with a nation's road network CCTV cameras) and detailed site hazard assessments for the (re)insurance sector.