Monitoring of forest resources through national forest inventory programmes is carried out in many countries. The expected climate changes will affect trees and forests and might cause an expansion of trees into presently treeless areas, such as above the current alpine tree line. It is therefore a need to develop methods that enable the inclusion of also these areas into monitoring programmes. Airborne laser scanning (ALS) is an established tool in operational forest inventories, and could be a viable option for monitoring tasks. In the present study, we used multi-temporal ALS data with point density of 8-15 points per m2, together with field measurements from single trees in the forest-tundra ecotone along a 1500-km-long transect in Norway. The material comprised 262 small trees with an average height of 1.78 m. The field-measured height growth was derived from height measurements at two points in time. The elapsed time between the two measurements was 4 years. Regression models were then used to model the relationship between ALS-derived variables and tree heights as well as the height growth. Strong relationships between ALS-derived variables and tree heights were found, with R 2 values of 0.93 and 0.97 for the two points in time. The relationship between the ALS data and the field-derived height growth was weaker, with R 2 values of 0.36-0.42. A cross-validation gave corresponding results, with root mean square errors of 19 and 11% for the ALS height models and 60% for the model relating ALS data to single-tree height growth.
Keywords: Forest inventory; LIDAR; Remote sensing; Tree line.