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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
Estimating tree diversity in forest ecosystems by two-phase inventories
Corona , P. , Fattorini , Lorenzo , Franceschi , Sara , Marcheselli , Marzia , Pisani , Caterina , Chiavetta , U. , Puletti , Nicola
biodiversity tessellation stratified sampling two-phase sampling
Mostra abstract
Several studies reveal that there is a strong interconnection between climate change and biodiversity. Indeed, estimating plant biodiversity is an important issue under forest ecosystem monitoring, which allows the evaluation of carbon storage and sequestration capacity. To this end, a two-phase strategy, suitably compatible with the most adopted sampling designs in large-scale forest inventories, is proposed. In the first phase, tessellation stratified sampling is performed by partitioning the study area into a grid of quadrats and by randomly selecting a point in each quadrat. The first-phase points are classified as forest or nonforest using remotely sensed imagery. In the second phase, a sample of points is selected from those classified as forest by means of simple random sampling without replacement. The second-phase points constitute the centers of circular plots that are visited in the field to record plant species (usually trees) and their abundance. Estimators of abundance and diversity and estimators of their variances are presented. The proposed strategy is applied in a forest area from Central Italy, as a case study. With respect to the sampling effort, the resulting estimates of relative standard errors are satisfactory, especially those regarding the overall total and diversity index estimators. The proposed statistical approach represents a suitable reference for integrated forest inventory frameworks effectively supporting biodiversity monitoring and assessment. © 2018 John Wiley & Sons, Ltd.
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2019
Rivista
Environmetrics
Dettagli
Vol. 30 (2)
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
Handbook of field sampling for multi-taxon biodiversity studies in European forests
Burrascano , Sabina , Trentanovi , Giovanni , Paillet , Yoan , Heilmann-Clausen , Jacob , Giordani , P. , Bagella , Simonetta , Bravo-Oviedo , Andrés , Campagnaro , Thomas , Campanaro , Alessandro , Chianucci , Francesco , de Smedt , Pallieter , Itziar , García Mijangos , Matošević , Dinka , Sitzia , Tommaso , Aszalós , Réka , Brazaitis , Gediminas , Cutini , Andrea , D'Andrea , Ettore , Doerfler , Inken , Hofmeister , Jeňýk , Hošek , Jan , Janssen , Philippe , Kepfer-Rojas , Sebastian , Korboulewsky , Nathalie , Kozák , Daniel , Lachat , Thibault , Lõhmus , Asko , López , Rosana , Mårell , Anders , Matula , Radim , Mikoláš , Martin , Munzi , Silvana , Nordén , Björn , Pärtel , Meelis , Penner , Johannes , Runnel , Kadri , Schall , Peter , Svoboda , Miroslav , Tinya , Flóra , Ujházyová , Mariana , Vandekerkhove , Kris , Verheyen , Kris , Xystrakis , Fotios , Ódor , Péter
biodiversity forest stand structure multi-taxon field methods indicators sampling protocol
Mostra abstract
Forests host most terrestrial biodiversity and their sustainable management is crucial to halt biodiversity loss. Although scientific evidence indicates that sustainable forest management (SFM) should be assessed by monitoring multi-taxon biodiversity, most current SFM criteria and indicators account only for trees or consider indirect biodiversity proxies. Several projects performed multi-taxon sampling to investigate the effects of forest management on biodiversity, but the large variability of their sampling approaches hampers the identification of general trends, and limits broad-scale inference for designing SFM. Here we address the need of common sampling protocols for forest structure and multi-taxon biodiversity to be used at broad spatial scales. We established a network of researchers involved in 41 projects on forest multi-taxon biodiversity across 13 European countries. The network data structure comprised the assessment of at least three taxa, and the measurement of forest stand structure in the same plots or stands. We mapped the sampling approaches to multi-taxon biodiversity, standing trees and deadwood, and used this overview to provide operational answers to two simple, yet crucial, questions: what to sample? How to sample? The most commonly sampled taxonomic groups are vascular plants (83% of datasets), beetles (80%), lichens (66%), birds (66%), fungi (61%), bryophytes (49%). They cover different forest structures and habitats, with a limited focus on soil, litter and forest canopy. Notwithstanding the common goal of assessing forest management effects on biodiversity, sampling approaches differed widely within and among taxonomic groups. Differences derive from sampling units (plots size, use of stand vs. plot scale), and from the focus on different substrates or functional groups of organisms. Sampling methods for standing trees and lying deadwood were relatively homogeneous and focused on volume calculations, but with a great variability in sampling units and diameter thresholds. We developed a handbook of sampling methods (SI 3) aimed at the greatest possible comparability across taxonomic groups and studies as a basis for European-wide biodiversity monitoring programs, robust understanding of biodiversity response to forest structure and management, and the identification of direct indicators of SFM. © 2021 The Authors
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2021
Rivista
Ecological Indicators
Dettagli
Vol. 132
DOI
ManFor C.Bd sites and the drivers of forest functions
Di Salvatore , Umberto , Tonti , Daniela , Bascietto , Marco , Chiavetta , U. , Cantiani , Paolo , Fabbio , Gianfranco , Becagli , Claudia , Bertini , Giada , Sansone , Dalila , Skudnik , Mitja , Kobal , Milan , Kutnar , Lado , Ferreira , Andreja , Kobler , Andrej , Kovač , Marko , Ferretti , Fabrizio
biodiversity italy silviculture slovenia carbon retention forest functions landscape driving forces silviculture driving forces life manfor c.bd management options
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2016
Rivista
Italian Journal of Agronomy
Dettagli
Vol. 11 (S1) pp. 64 - 95
Ecological portrayal of old-growth forests and persistent woodlands in the cilento and vallo di Diano National Park (southern Italy)
Marchetti , Marco , Tognetti , Roberto , Lombardi , Fabio , Chiavetta , U. , Palumbo , Giuseppe , Sellitto , Vincenzo Michele , Colombo , C. Massimo , Iovieno , Paola , Alfani , Anna , Baldantoni , Daniela , Barbati , Anna , Ferrari , Barbara , Bonacquisti , Sandro , Capotorti , Giulia , Copiz , Riccardo , Blasi , Carlo
biodiversity mediterranean region ecological characterization managed stands old-growth forests persistent woodlands soil
Mostra abstract
The maintenance of certain levels of old forest represents a cornerstone of the EU's biodiversity management strategy. A consensus on a single general ecological definition of old-growth is particularly difficult in Mediterranean Europe. The present paper deals with old-growth forests and persistent woodlands in the Cilento and Vallo di Diano National Park (PNCVD) to give an ecological understanding of forest complexity and dynamics under a multiscale and multidisciplinary perspective. The multiscale approach ranged from the identification and mapping of potential old-growth stands at landscape scale to a two-level field review of forest stand features. Field sampling involved a multidisciplinary team of researchers in forest structure, pedologic environment, soil microbial activity, flora and vegetation and deadwood components. The research provided sound knowledge about old-growthness features in the PNCVD that constitutes a unique case study in the whole Mediterranean basin. The integration of results allowed to: identify main ecosystem functions and the related services of the old-growth forests in the study area; distinguish persistent woodlands, multi-aged stands with old trees deriving from nineteenth-century management practices, from old-growth forests sensu strictu; recognize indicators of direct and indirect impacts of human activities; suggest effective practices for sustainable management in the Mediterranean context. © 2010 Società Botanica Italiana.
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2010
Rivista
Plant Biosystems
Dettagli
Vol. 144 (1) pp. 130 - 147
DOI