Use of ground and LiDAR data to model the NPP of a Mediterranean pine forest

This letter presents the application of a recently developed methodology to predict the net primary production (NPP) of a Mediterranean pine forest in San Rossore, Central Italy. The methodology is based on the use of two models, C-Fix and BIOME-BGC, whose outputs are combined with estimates of stand volume and age to describe the actual trophic status of the examined ecosystems. This work investigates the possibility of deriving these two forest attributes from airborne high-resolution Light Detection and Ranging (LiDAR) data. Specifically, stand volume and age estimates are obtained by linear transformation of LiDAR average and maximum stand canopy heights, respectively. The NPP modelling strategy driven by these estimates yields results that are evaluated by comparison with ground measurements of current annual increment. The success of this test opens the way to integrate ecosystem modelling techniques and LiDAR data for simulating net forest carbon fluxes.