Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data

Abstract

Site index (SI) is a common measure of forest site productivity, serving as a valuable baseline for forest management. The main objective of this study was to develop a SI model for Pinus pinaster Ait. in north-west Spain by combining bi–temporal, low–density airborne laser scanning (ALS) data (acquired in the periods 2009–2011 and 2015–2017) with climatic, edaphic and physiographical data. Site productivity, assessed by site quality curves, was modelled using an age-independent difference equation method based on ALS metrics and environmental variables. For the model development process, we used data from 156 sample plots in pure and even-aged P. pinaster stands distributed throughout Galicia (NW Spain) and measured in the Spanish National Forest Inventory (SNFI). The generalized algebraic difference approach (GADA) formulation was tested by using two different base equations for modelling the dominant height growth (ΔH) from ALS variables. The GADA formulation derived from the Bertalanffy’s base model produced the best estimates of dominant height (H) for P. pinaster stands in Galicia. Use of the proposed model to estimate ΔH for a new pine stand requires two ALS data sets for estimating site-specific (local) parameters. To enable use of the model when such information is not available, the relationship between the values of the site-specific parameter and environmental variables was described using Multivariate Adaptive Regression Splines (MARS). Use of the MARS equation enabled us to develop spatially-explicit predictive maps of the site-specific parameter values, which can be used together with the GADA model to derive ΔH curves and SI estimates for P. pinaster stands in the whole study region.