Title:	Laser Scanning Data Processing
DNr:	NAISS 2025/22-240
Project Type:	NAISS Small Compute
Principal Investigator:	Vincent Buness <vincent.buness@slu.se>
Affiliation:	Sveriges lantbruksuniversitet
Duration:	2025-02-14 – 2026-03-01
Classification:	10611
Keywords:

Abstract

For the FORMAS project “Bedömning av samband och avvägningar mellan produktivitet, klimateffekter och biodiversitet,” we propose to process terrestrial laser scanning (TLS) point clouds stored in *.laz format, totaling approximately 100 GB. Because personal computers lack sufficient RAM to handle these large datasets within RStudio, we request access to high-performance server resources. Our planned workflow involves a single-pass processing strategy in RStudio. Raw TLS files will be loaded from an external hard drive, processed via an R script—applying steps such as ground classification, height normalization, and spatial clipping to a 30 m effective area—and then the processed files will be saved back to the external drive. Finally, we will compute a suite of forest structural indices for 36 TLS files, enabling us to quantify canopy characteristics and forest heterogeneity. By leveraging server capacities, we can efficiently manage and analyze these extensive TLS datasets, ensuring robust, reproducible, and scalable assessments of forest productivity, climate impacts, and biodiversity.