Dataset - Prediction of stand-level growing stock by using a spatial regression model in an Austrian protection forest

This dataset contains input data, intermediate products, and model outputs used in the study“Prediction of stand-level growing stock by using a spatial regression model in an Austrian protection forest”. The archive is organized into four main folders: Coordinates.zip – KML file with the geographic locations of all forest inventory plots. GeoData.zip – Airborne Laser Scanning derived raster layers used for spatial modeling. RData.zip – Intermediate products, leave-one-out cross-validation predictions and reference growing stock values at plot level. TreeData.zip – Tree-level structural variables derived from Personal Laser Scanning for each inventory plot. Each folder contains a dedicated README file describing the file structure, variables, and data content in detail. Together with the comprehensive description of model selection, parameter settings, and statistical methodology provided in the linked journal article, this dataset enables full reproducibility of the spatial modeling workflow and growing stock estimation. The raw PLS point cloud data are not included due to file size and usability constraints, but can be made available upon reasonable request to the corresponding author.