Benchmarking tree species classification from proximally sensed laser scanning data: Introducing the FOR ‐ species20K dataset

作者：Stefano Puliti, Emily R. Lines, Jana Müllerová, Julian Frey, Zoe Schindler, Adrian Straker, Matthew J. Allen, Lukas Winiwarter, Nataliia Rehush, Hristina Hristova, Brent A. Murray, Kim Calders, Nicholas C. Coops, Bernhard Höfle, Liam Irwin, Samuli Junttila, Martin Krůček, Grzegorz Krok, Kamil Král, Shaun R. Levick, Linda Lück, Azim Missarov, Martin Mokroš, Harry Owen, Krzysztof Stereńczak, Timo Pitkänen, Nicola Puletti, Ninni Saarinen, Chris Hopkinson, Louise Terryn, Chiara Torresan, Enrico Tomelleri, Hannah Weiser, Rasmus Astrup · 发表于：Methods in Ecology and Evolution · 年份：2025 · DOI：10.1111/2041-210x.14503 · 被引用次数：43 · 研究领域：Remote Sensing and LiDAR Applications、Forest Ecology and Biodiversity Studies、Forest ecology and management

Abstract Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single‐tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification. To address the above limitations, we compiled the FOR‐species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR‐species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP‐Mixer, DGCNNs) and multi‐view 2D‐ba...