A Reproducible End-to-End Airborne LiDAR Workflow for Forest Structure Mapping

Abstract. Airborne LiDAR enables direct measurement of canopy height and three-dimensional forest structure, but many LiDAR-based studies remain difficult to reproduce due to ad hoc processing decisions and limited pipeline transparency (White et al., 2019). This study presents a reproducible end-to-end workflow that transforms raw LAS point clouds into ecologically interpretable forest structure products. Using the Petawawa Research Forest (PRF) in Ontario as a case study (Natural Resources Canada, 2023; MacLean et al., 2019; Pickering, 2012), the pipeline integrates data ingestion and quality control, ground classification and height normalization using PMF and SMRF filters (Zhang et al., 2003; Pingel et al., 2013), canopy height model generation, canopy density and gap metrics, vertical structural complexity via Shannon entropy, and area-based plot- and stand-level summaries. The workflow also supports rule-based species-group mapping and automated stand delineation for forest inventory applications. Sensitivity to key processing parameters is evaluated to support transparent and defensible long-term forest monitoring (Canadian Forest Service, 2005).