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Benchmarking tree species classification from proximally sensed laser scanning data: Introducing the FOR-species20K dataset
Puliti , Stefano , Lines , Emily R. , Müllerová , Jana , Frey , Julian , Schindler , Zoe , Straker , Adrian , Allen , Matthew J. , Winiwarter , Lukas , Rehush , Nataliia , Hristova , Hristina S. , Murray , Brent A. , Calders , Kim , Coops , Nicholas C. , Höfle , Bernhard , Irwin , Liam A.K. , Junttila , Samuli , Kruček , Martin , Krok , G. , Král , Kamil , Levick , Shaun R. , Lück , Linda , Missarov , Azim , Mokroš , M. , Owen , Harry Jon Foord , Stereńczak , Krzysztof Jan , Pitkänen , Timo P. , Puletti , Nicola , Saarinen , Ninni , Hopkinson , Chris Dennis , Terryn , Louise , Torresan , C. , Tomelleri , Enrico , Weiser , Hannah , Astrup , Rasmus
lidar remote sensing biodiversity deep learning point cloud classification single-tree inventory
Mostra 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-based methods (SimpleView, DetailView, YOLOv5). 2D Image-based models had, on average, higher overall accuracy (0.77) than 3D point cloud-based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top-scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes. The FOR-species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state-of-the-art of point cloud tree species classification methods. © 2025 The Author(s). Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
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2025
Rivista
Methods in Ecology and Evolution
Dettagli
Vol. 16 (4) pp. 801 - 818
DOI
Assessment of UAV photogrammetric DTM-independent variables for modelling and mapping forest structural indices in mixed temperate forests
Giannetti , Francesca , Puletti , Nicola , Puliti , Stefano , Travaglini , Davide , Chirici , Gherardo
biodiversity precision forestry forest structure forest inventory airborne laser scanning drone dtm-independent structure from motion
Mostra abstract
In the EU 2020 biodiversity strategy, maintaining and enhancing forest biodiversity is essential. Forest managers and technicians should include biodiversity monitoring as support for sustainible forest management and conservation issues, through the adoption of forest biodiversity indices. The present study investigates the potential of a new type of Structure from Motion (SfM) photogrammetry derived variables for modelling forest structure indicies, which do not require the availability of a digital terrain model (DTM) such as those obtainable from Airborne Laser Scanning (ALS) surveys. The DTM-independent variables were calculated using raw 3D UAV photogrammetric data for modeling eight forest structure indices which are commonly used for forest biodiversity monitoring, namely: basal area (G); quadratic mean diameter (DBH<inf>mean</inf>); the standard deviation of Diameter at Breast Height (DBH<inf>σ</inf>); DBH Gini coefficient (Gini); the standard deviation of tree heights (H<inf>σ</inf>); dominant tree height (H<inf>dom</inf>); Lorey's height (H<inf>l</inf>); and growing stock volume (V). The study included two mixed temperate forests areas with a different type of management, with one area, left unmanaged for the past 50 years while the other being actively managed. A total of 30 field sample plots were measured in the unmanaged forest, and 50 field plots were measured in the actively managed forest. The accuracy of UAV DTM-independent predictions was compared with a benchmark approach based on traditional explanatory variables calculated from ALS data. Finally, DTM-independent variables were used to produce wall-to-wall maps of the forest structure indices in the two test areas and to estimate the mean value and its uncertainty according to a model-assisted regression estimators. DTM-independent variables led to similar predictive accuracy in terms of root mean square error compared to ALS in both study areas for the eight structure indices (DTM-independent average RMSE<inf>%</inf> = 20.5 and ALS average RMSE<inf>%</inf> = 19.8). Moreover, we found that the model-assisted estimation, with both DTM-independet and ALS, obtained lower standar errors (SE) compared to the one obtained by model-based estimation using only field plots. Relative efficiency coefficient (RE) revealed that ALS-based estimates were, on average, more efficient (average RE ALS = 3.7) than DTM-independent, (average RE DTM-independent = 3.3). However, the RE for the DTM-independent models was consistently larger than the one from the ALS models for the DBH-related variables (i.e. G, DBH<inf>mean</inf>, and DBH<inf>σ</inf>) and for V. This highlights the potential of DTM-independent variables, which not only can be used virtually on any forests (i.e., no need of a DTM), but also can produce as precise estimates as those from ALS data for key forest structural variables and substantially improve the efficiency of forest inventories. © 2020 Elsevier Ltd
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2020
Rivista
Ecological Indicators
Dettagli
Vol. 117
DOI
Managed forests are a stronghold of non-native beetles in Europe
Basile , Marco , Lachat , Thibault , Balducci , Lorenzo , Chianucci , Francesco , Chojnacki , Lucas , Archaux , Frédéric , N Avtzis , Dimitrios N. , Bouget , Christophe , de Smedt , Pallieter , Doerfler , Inken , Dumas , Yann , Elek , Zoltán , Gosselin , Marion , Goßner , Martin M. , Heilmann-Clausen , Jacob , Hofmeister , Jeňýk , Hošek , Jan , Janssen , Philippe , Justesen , Mathias Just , Hansen , Aslak Kappel , Schmidt , Inger Kappel , Kepfer-Rojas , Sebastian , Mårell , Anders , Matula , Radim , Müller , Jörg C. C. , Nordén , Björn , Ódor , Péter , Paillet , Yoan , Ravera , Sonia , Sitzia , Tommaso , Tinya , Flóra , Burrascano , Sabina , Brockerhoff , Eckehard G.
biodiversity biological invasions biotic resistance coleoptera unmanaged forests vascular plants
Mostra abstract
The species richness of vascular plants in forests can have contrasting effects on the occurrence of non-native insects. The establishment of non-native insect populations may be facilitated by low plant species richness, which reflects the availability of few but easily accessible resources, or hampered by high plant species richness due to spatial dilution of resources or biotic resistance (i.e., resistance against biological invasions). The relationship between the species richness of plants and non-native insects is likely influenced by disturbance regimes, which, in European forests, mostly consists of timber harvesting. We investigated this relationship considering two major forest attributes: (i) species richness of non-native vascular plants and (ii) forest management. From 1101 forest plots in Europe, we gathered occurrences of 1212 vascular plant species, including 160 non-native species, and of 2404 beetle species, including 29 non-native species. We tested the relationship between the species richness of non-native beetles and plants using non-linear quantile regressions. We disentangled the effect of non-native plant species richness from that of management on the species richness of non-native beetles, while accounting for forest structural variables, using structural equation models. We found clear evidence of a hump-shaped relationship between non-native beetle and plant species richness. The general shape of the relationship persisted when considering only woody or non-woody plants, as well as only non-native plants. The relationship was also similar between managed and unmanaged forests. However, the proportion of non-native beetles in managed forests was higher than in unmanaged forests at the same plant species richness. Management had a direct negative effect on non-native beetle species richness, whereas non-native plant species richness had a direct positive effect. When considering all direct and indirect effects, management facilitated the occurrence of non-native beetles indirectly via non-native plants rather than directly. Synthesis and applications. Species richness of native and non-native vascular plants modulates the species richness of non-native beetles through relationships with opposite signs. The interplay with management regimes and forest structures determines whether non-native beetles are promoted. Forest management aimed at reducing the intensity of disturbance while encouraging native plant species richness could promote the dominance of dilution effects and biotic resistance and could moderate the establishment of non-native insects. © 2025 The Author(s). Journal of Applied Ecology © 2025 British Ecological Society.
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2025
Rivista
Journal of Applied Ecology
Dettagli
Vol. 62 (5) pp. 1243 - 1257
DOI