Modelling top height growth and site index using repeated laser scanning data

Abstract

Forest site productivity, which is a quantitative estimate of the potential of a site to produce plant biomass, remains a fundamental variable in forestry. The most commonly used and widely accepted method of evaluating site productivity is the site index. Therefore, the construction of site index models describing top height (TH) growth with age remains a fundamental task for site productivity differentiation. Three main data sources have been used for site index model development to date: (1) repeated measurements on permanent sample plots (PSP); (2) temporary sample plot (TSP) data from periodic inventories; and (3) stem analysis (SA) data. Our study is practical application of change detection using airborne laser scanners for the development of top height growth models. We demonstrated how wall-to-wall airborne laser scanner (ALS) data obtained for large forest areas can be used in developing top height growth models for Norway spruce that appropriately reflect site-specific growth trajectories. Site specific growth trajectories were successfully captured by repeated height measurements using ALS data from notably short 5-year period, which indicates that such a period between subsequent ALS observations is sufficient and surmounts the noise and other uncertainties connected with ALS systems and interannual TH growth variations. Height increment obtained by change detection using repeated airborne laser scanning (ALS) may be recognized as a new, fully valuable data source for TH growth and site index modelling. Repeated ALS observations can be a substitute for height growth data used in site index modelling and collected to-date from SA, PSP or TSP. It could be expected that improving ALS technologies, decreasing costs of laser scanning acquisition and increasing data availability will result in improving the accuracy of forest height growth estimates. Therefore, in the near future, both utility and increased predictive validity will lead to substantial increases in the importance of change detection using airborne laser scanners in forest growth modelling using the data from repeated ALS measurements.