This repository contains the Jupyter notebooks for processing country-wide ALS point clouds of the Netherlands (AHN1–AHN4), together with the scripts for downloading AHN raw point cloud (.LAZ files) and generating road/water/building as well as powerline masks. Two use cases utilizing the generated data products were demonstrated in a recently submitted manuscript, and the R scripts are also provided here.
Four country-wide airborne laser scanning surveys were conducted by Actueel Hoogtebestand Nederland, providing detailed topographic and ecosystem structure information over the past two decades (1996–2022). We employed an open-source high-throughput workflow Laserfarm (based on the Laserchicken software), to process around 70 TB point clouds into ready-to-use raster layers (LiDAR metrics) at 10 m resolution (~ 59 GB), enabling a wide use and uptake of ecosystem structure information in biodiversity and habitat monitoring, ecosystem and carbon dynamic modeling. Four sets of 25 LiDAR-derived vegetation metrics were generated, representing ecosystem height, cover, and structural variability.
The generated data products are made publically available on Zenodo https://doi.org/10.5281/zenodo.13940846