Country-wide data of ecosystem structure from the fourth Dutch airborne laser scanning survey (AHN4)

This data repository contains country-wide data products for the ecosystem structure metrics generated from Airborne Laser Scanning (ALS) data across the Netherlands (AHN4). Twenty-five ecosystem structure metrics (at 10-meter resolution, GeoTIFF format) were derived from the AHN4 dataset (https://www.ahn.nl/ahn-viewer) using Laserfarm workflow (https://zenodo.org/record/5636773). Laserfarm is a free and open-source workflow that enables efficient, scalable, and distributed processing of multi-terabyte LiDAR point clouds from national and regional ALS surveys into LiDAR metrics of ecosystem structure. All code of Laserfarm is hosted and freely available on GitHub (https://github.com/eEcoLiDAR/Laserfarm). Note that we also published the data products generated from AHN3 (2014-2019), which you can find in the repository here: https://doi.org/10.5281/zenodo.6421381. Laserfarm workflow was also employed to generate the data products from AHN4 (2020-2022). The twenty-five LiDAR metrics are related to three key dimensions of ecosystem structure (ecosystem height, ecosystem cover, and ecosystem structural complexity). Each GeoTIFF layer represents one LiDAR metric at 10 m resolution covering the whole Netherlands (file name as "ahn4_10m_featrue_name.tiff"). A detailed description of all the metrics can be found in the README file (README.pdf). Relevant publications: Kissling, W.D., Shi, Y., Koma, Z., Meijer, C., Ku, O., Nattino, F., Seijmonsbergen, A.C., & Grootes, M.W. (2022). Laserfarm – A high-throughput workflow for generating geospatial data products of ecosystem structure from airborne laser scanning point clouds. Ecological Informatics, 72, 101836 (https://doi.org/10.1016/j.ecoinf.2022.101836) Kissling, W.D., Shi, Y., Koma, Z., Meijer, C., Ku, O., Nattino, F., Seijmonsbergen, A.C., & Grootes, M.W. (2023). Country-wide data of ecosystem structure from the third Dutch airborne laser scanning survey. Data in Brief, 46, 108798 (https://doi.org/10.1016/j.dib.2022.108798)