Estimation of periodic annual increment of tree ring widths by airborne laser scanning

Most forest growth studies using airborne laser scanning (ALS) consider how the changes in forest attributes are observed in repeated ALS data acquisitions, but the prediction of future forest growth from ALS data is still a rarely discussed topic. This study examined the prediction of the periodic annual increment (PAI) of the width of tree rings over a period of 10 years. The requirement for this approach is that ALS data are acquired at the beginning of the growth period. This is followed by field measurements of growth by drilling after a given growth period. The PAI was modelled in terms of ALS metrics by using the principle of the area-based approach. The metrics related to intensity were particularly significant as predictors, whereas the effective leaf area index was not. The root-mean-square error (RMSE) of the predictions was slightly over 21%. Additional field information (soil type, management operations) improved the RMSE by 2.7 percentage units.

Automated summary

This study examines the prediction of future forest growth using ALS data by measuring the periodic annual increment (PAI) of tree ring width. The results show that metrics related to intensity play a significant role in the prediction, while the effective leaf area index is not important. Additional field information can improve the accuracy of the predictions.