From point clouds to forest management: Quantifying the sensitivity of a decision support framework to initialization data using close-range remote sensing

This dataset supports the analysis presented in "From point clouds to forest management: Quantifying the sensitivity of a decision support framework to initialization data using close-range remote sensing" (https://doi.org/10.1016/j.ecoinf.2026.103896). The repository covers two parts of the analysis: (1) data preparation from LiDAR-based forest inventories, and (2) sensitivity analysis of decision support system (DSS) outputs. The intermediate forest simulation (ForClim v4.1) and multi-criteria decision analysis (MCDA) were carried out using an external pipeline described in Blattert et al. (2024), using the R package rforclim (v1.01.001) by Hiltner & Marano (2025). The corresponding model outputs are included here as inputs to the sensitivity analysis, making all analyses in this repository fully reproducible without requiring access to the simulation pipeline. The ForClim model (v4.1) (Marano et al., 2025) is openly available from the ETH Zurich Institute of Terrestrial Ecosystems (https://ites-fe.ethz.ch/openaccess/products/forclim). Climate data were sourced from the publicly available Swiss CH2018 dataset (CH2018 Project Team, 2018). Soil data were sourced from Baltensweiler