Weather-sensitive height growth modelling of Norway spruce using repeated airborne laser scanning data

Abstract

Fluctuations in weather conditions, particularly precipitation and water availability, may strongly affect growth rate patterns and lead to interannual height growth variation. Consequently, height growth models developed using airborne laser scanning (ALS) data collected at short time intervals may over- or underestimate long-term height growth trends and finally result in different growth forecasts. The objective of this study was to develop height growth models for Norway spruce, including the effect of weather conditions. We used ALS-derived top height (TH) estimates and meteorological data from the research area collected for 2007-2012 and 2013-2018 to develop a weather-sensitive height growth model. The top height (TH) growth of Norway spruce was affected by the mean annual precipitation sum (APS) in the studied periods, and a higher APS resulted in faster TH growth. This study demonstrates the high potential of repeated ALS for detecting short-term variation in the tree height increment and the development of weather-sensitive height growth models.