This benchmark dataset was acquired during the SilviLaser conference 2021 in Vienna. The benchmark aims to demonstrate the different terrestrial system's capabilities for capturing 3D scenes in various forest conditions. A number of universities, institutes, and companies participated and contributed their outputs to this dataset, compiled by terrestrial laser scanning (TLS), mobile laser scanning (MLS), as well as terrestrial photogrammetric systems (TPS). Along with the terrestrial data, one airborne laser scanning (ALS) data was provided as a reference. Eight forest plots were installed in the terrestrial challenge. Each plot was formed with a 25-meter radius circular area and different tree species (i.e. spruce, pine, beech, white fir), forest structures (i.e. one layer, multi-layer, natural regeneration, deadwood), and age classes (~50 – 120 years). The 3D point clouds acquired by each participant cover the eight plots. In addition to point clouds, traditional in-situ data (tree position, tree species, DBH) were recorded by the organization team. All point clouds provided by participants were processed in the following steps: co-registration with geo-referenced data, setting a uniform coordinate reference system (CRS), and removing data located out of the plot. This work was performed by OPALS, a laser scanning data processing software developed by the Photogrammetry Group of the TU Wien Department of Geodesy and Geoinformation. Please note that some point clouds are not archived due to problems encountered during pre-processing. The final products consist of one metadata, 3D point clouds, ALS data for reference, and corresponding digital terrain models (DTM) derived from the ALS data using OPALS software. Point clouds are in laz 1.4 format, and DTMs are raster models in GeoTIFF format. Furthermore, all geo-data use CRS of WGS84 / UTM zone 33N (EPSG:32633). More information (e.g. instrument, point density, and extra attributes) can be found in the file "SL21BM_TER_metadata.csv". This dataset is available to the community for a wide variety of scientific studies. These unique data sets will also form the basis for an international benchmark for parameter retrieval from different 3D recording methods. Acknowledgements This dataset was contributed by the universities/institutes/companies (alphabetical order):

Czech University of Life Sciences Prague Forest Design Green Valley International RIEGL Silva Tarouca Research Institute Swiss Federal Institute for Forest, Snow and Landscape Research Umweltdata GmbH University of Natural Resources and Life Sciences Wageningen University & Research Notes

In terms of in-situ data, please contact Markus Hollaus for details. To perform a bulk download, please use this file to get the URL list. Changelog

v1.0    First release v1.1    Fix the misalignment issue for plot D