Data for benchmarking tree species classification from proximally-sensed laser scanning data.
- FOR-species20K dataset
- S Puliti - Norwegian Institute of Bioeconomy ResearchE Lines - University of CambridgeJ Müllerová - Jan Evangelista Purkyně University in Ústí nad LabemJ Frey - University of FreiburgZ Schindler - University of FreiburgA Straker - University of GöttingenJM AllenL WiniwarterN Rehush - Swiss Federal Institute for Forest, Snow and Landscape ResearchH Hristova - Swiss Federal Institute for Forest, Snow and Landscape ResearchB Murray - University of British ColumbiaK Calders - Ghent UniversityL Terryn - Ghent UniversityN Coops - University of British ColumbiaB Höfle - Heidelberg UniversityS Junttila - University of Eastern FinlandM Krucek - Landscape Research InstituteG KrokK Král - Landscape Research InstituteRS LevickL Luck - Charles Darwin UniversityA Missarov - Landscape Research InstituteM Mokroš - University College LondonH Owen - University of CambridgeK StereńczakT Pitkänen - Natural Resources Institute FinlandN Puletti - Consiglio per la ricerca in agricoltura e l’analisi dell’economia agrariaN Saarinen - University of Eastern FinlandC Hopkinson - University of LethbridgeC Torresan - National Research CouncilEnrico Tomelleri - Free University of Bozen-BolzanoH Weiser - Heidelberg UniversityR Astrup - Norwegian Institute of Bioeconomy Research
- (UNIBZ)94173988
991007436523901241 - Faculty of Agricultural, Environmental and Food Sciences
- English
- Dataset
- Puliti S, Lines E, Müllerová J, Frey J, Schindler Z, Straker A, Allen JM, Winiwarter L, Rehush N, Hristova H, Murray B, Calders K, Terryn L, Coops N, Höfle B, Junttila S, Krucek M, Krok G, Král K, Levick RS, Luck L, Missarov A, Mokroš M, Owen H, Stereńczak K, Pitkänen T, Puletti N, Saarinen N, Hopkinson C, Torresan C, Tomelleri E, Weiser H, Astrup R
- description: Data split and usage The data is split into: Development data (dev): these includes 90% of the trees in the dataset and consists of individual tree point clouds (*.laz) named according to the treeID column available in the tree_metadata_dev.csv file, from which tree_species labels are available. These data are meant to be used for model development and can thus be further split into training and validation datasets. Test data (test): these are 10% of the trees (balanced sample) and include individual tree point clouds (*.laz) but, for benchmarking purposes, the species labels are witheld for benchmarking purposes. Thus to make use of the test data the users should predict species on the test trees, and output a table (.csv file) with a row per predicted tree and two columns (treeID and predicted_species). This table can then be used to create a new submission in the FOR-species20K Codabench benchmarking platform and obtain the evaluation metrics corresponding to the test data. Cite Any scientific publication using the data should cite the following paper: Puliti, S., Lines, E., Müllerová, J., Frey, J., Schindler, Z., Straker, A., Allen, M.J., Winiwarter, L., Rehush, N., Hristova, H., Murray, B., Calders, K., Terryn, L., Coops, N., Höfle, B., Krůček, M., Krokm, G., Král, K., Luck, L., Levick, S.R., Missarov, A., Mokroš, M., Owen, H., Stereńczak, K., Pitkänen, T.P., Puletti, N., Saarinen, N., Hopkinson, C., Torresan, C., Tomelleri, E., Weiser, H., Junttila, S., and Astrup, R. (2025) Benchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset. Methods in Ecology and Evolution, 00,1–18. 10.5281/zenodo.13255198