Modelling individual tree diameter growth based on airborne laser scanning data

Precise tree growth projections are needed for silvicultural decision-making, but also for climate change mitigation efforts. The use of remotely-sensed data, especially from airborne laser scanning (ALS), has revolutionised the collection of forest information by capturing detailed structural information. Thus, it is appealing to use ALS data to construct new tree growth models. In this study, we constructed three different diameter growth models based on field measurements and ALS data collected in 2009 and 2014, i.e., before the growth period examined (2014–2019). Our aims were to compare field measurements and ALS data and estimate whether field measurements can be replaced with ALS data in tree diameter growth projections. The differences between the models were minor, with RMSE values being approximately 55% across all models. The prediction accuracy was modest, likely due to limited data, uneven ALS data quality, and possible issues in tree detection and crown delineation. As the differences between the models were minor, we conclude that ALS data could provide a feasible alternative to field measurements. In addition, an ALS time-series variable representing height growth prior to the study period was statistically significant, which is promising for the development of further ALS-based growth models.