Mapping Windthrow Risk in Pinus radiata Plantations Using Multi-Temporal LiDAR and Machine Learning: A Case Study of Cyclone Gabrielle, New Zealand - Michael S. Watt; Andrew Holdaway; Nicolò Camarretta; Tommaso Locatelli; Sadeepa Jayathunga; Pete Watt; Kevin Tao; Juan C. Suárez (Remote Sensing)
As the frequency of strong storms and cyclones increases, understanding wind risk in both existing and newly established plantation forests is becoming increasingly important. Recent advances in the quality and availability of remotely sensed data have significantly improved our capability to make large-scale wind risk predictions. This study models the loss of radiata pine (Pinus radiata D.Don) plantations following a severe cyclone within the Gisborne Region of New Zealand through leveraging repeat regional LiDAR acquisitions, optical imagery, and various surfaces describing key climatic, topographic, and storm-specific conditions. A random forest model was trained on 9713 plots classified as windthrow or no-windthrow. Model validation using 50 iterations of 80/20 train/test splits achieved robust accuracy (accuracy = 0.835; F1 score = 0.841; AUC = 0.913). In comparison to most European empirical models (AUC = 0.51–0.90), our framework demonstrated superior discrimination, underscoring its value for regions prone to cyclones. Among the 14 predictor variables, the most influential were mean windspeed during February, the wind exposition index, site drainage, and stand age. Model predictions closely aligned with the estimated 3705 hectares of cyclone-induced forest damage and indicated that 20.9% of unplanted areas in the region would be at risk of windthrow at age 30 if established in radiata pine. The resulting wind risk surface serves as a valuable decision-support tool for forest managers, helping to mitigate wind risk in existing forests and guide adaptive afforestation strategies. Although developed for radiata pine plantations in New Zealand, the approach and findings have broader relevance for forest management in cyclone-prone regions worldwide, particularly where plantation forestry is widely practised.