Search Results (97)

Urban mediterranean forests are key components of urban ecosystems. Accurate, high-resolution data on forest structural attributes are essential for effective management. This study evaluates the efficiency of unmanned laser scanning systems (ULS) and terrestrial LiDAR (TLS) in deriving key tree attributes, diameter at breast height (DBH) and tree height, within a small urban park in Zadar, Croatia. Accuracy assessment of the ULS and TLS-derived DBH was conducted based on traditional ground-based measurement (TGBM) data. For ULS, an automatic Spatix workflow was applied that classified points into a Tree class, segmented trees using trunk-based logic, and estimated DBH by fitting a circle to a 1.3 m slice; tree height was computed from the ground-normalized cloud with the Output Tree Cells tool. A semi-automatic CloudCompare/ArcMap workflow used CSF ground filtering, Connected Components segmentation, extraction of a 10 cm slice, manual trunk vectorization, and DBH calculation via Minimum Bounding Geometry. TLS scans, processed in FARO SCENE, were then analyzed in Spatix using the same automatic trunk-fitting procedure to derive DBH and height. Accuracy for DBH was evaluated against TGBM; comparative performance was summarized with standard error metrics, while ULS and TLS tree heights were compared using Concordance Correlation Coefficient (CCC) and Bland–Altman statistics. Results indicate that the semi-automatic approach outperformed the automatic approach in deriving DBH. TLS-derived DBH values demonstrated higher consistency and agreement with TGBM, as evidenced by their strong linear correlation, minimal bias, and narrow residual spread, while ULS exhibited greater variability and systematic deviation. Tree height comparisons between ULS and TLS revealed that ULS consistently produced slightly higher and more uniform measurements. This study highlights limitations in the evaluated techniques and proposes a hybrid approach combining ULS scanning with personal laser scanning (PLS) systems to enhance data accuracy in urban forest assessments. Full article

The growing implementation of close-to-nature forestry practices in the management of northern forests, characterized by dispersed harvesting operations, has heightened the importance of minimizing damage to residual stands as a key aspect of sustainable forest management. The objective of this study is to examine and compare the resistance of various tree species and diameter classes to wounds incurred during logging operations of differing sizes, intensities, and locations. In addition, the research aims to assess temporal changes in wound characteristics, including healing and closure processes, across species. This long-term, 18-year investigation was conducted in the Kheyrud Forest, located within the Hyrcanian broadleaf forest region of northern Iran, to evaluate the dynamics of wound healing in residual trees following ground-based skidding operations. Through a comprehensive assessment of 272 wounded trees across six species, we demonstrate that species significantly influences healing ratio (Kruskal–Wallis, p < 0.01), with Oriental beech (Fagus orientalis Lipsky) (50.6%) showing superior recovery compared to the Chestnut-leaved oak (Quercus castaneifolia) (37.5%). Healing ratio decreased with larger diameter at breast height (DBH) (R² = 0.114, p < 0.01), while absolute healed area increased. Larger areas (>1000 cm²) reduced healing by 42.3% versus small wounds (<500 cm²) (R² = 0.417, p < 0.01). Severe wounds (deep gouges) showed 19% less healing than superficial injuries (p = 0.003). Circular wounds healed significantly better than rectangular forms (χ² = 24.92, p < 0.001). Healing ratio accelerated after the first decade, reaching 69% by year 17 (R² = 0.469, p < 0.01). Wound height (p = 0.117) and traffic intensity (p = 0.65) showed no statistical impact. Contrary to expectations, stem position had no significant effect on wound recovery, whereas wound geometry proved to be a critical determinant. The findings highlight that appropriate species selection, minimizing wound size (to less than 500 cm²), and adopting extended cutting cycles (exceeding 15 years) are essential for enhancing residual stand recovery in close-to-nature forestry systems. Full article

Accurate stem-volume estimation supports inventory, valuation and carbon accounting, but Pressler’s single-section formula has never been tested in the highly productive European-beech forests of the Central Rhodope Mountains, Greece. We quantified the bias of Pressler estimates and developed size-specific correction factors. Sixty Fagus sylvatica L. trees felled in 2023–2024 were measured destructively at 1-m intervals. Pressler standing volumes were compared with Smalian-plus-cone reference volumes (hereafter referred to as true volumes) and analysed with generalized additive models. Pressler underestimated true volume (mean bias = −0.088 m³; RMSE = 0.204 m³; MAPE = 21%). Under-estimation increased with diameter. A GAM with DBH and height explained 96.7% of the variance in true volume. We also fit a Random Forest as a complementary check. Multipliers of 1.30 (<25 cm DBH), 1.20 (25–45 cm), 1.30 (45–55 cm) and ≥1.35 (≥55 cm) cut residual error to ≤20% overall and <10% inside the well-sampled 35–45 cm class. A simple DBH-class correction table restores Pressler’s speed while meeting modern accuracy standards for inventory and carbon reporting. Full article

Chinese fir, as a crucial fast-growing tree species in the hilly regions of southern China, exhibits spatial structure characteristics that directly influence both the ecological functionality and productivity of its stands. This study focused on Chinese fir plantations in the Yangkou State-Owned Forest Farm, Fujian Province. Using UAV-LiDAR point cloud data, individual tree parameters such as height and crown width were extracted, and a DBH inversion model was constructed by integrating machine learning algorithms. Spatial structure parameters were quantified through weighted Voronoi diagrams. A comprehensive evaluation system was established based on the combined weighting method and fuzzy evaluation model to systematically analyze spatial structure characteristics and their evolutionary patterns across different age classes. The results demonstrated that growth environment indicators (openness and openness ratio) progressively declined with the stand’s age, reflecting deteriorating light conditions due to increasing canopy closure. Growth superiority (size ratio and angle competition index) exhibited a “V”-shaped trend, with the most intense competition occurring in the middle-aged stands before stabilizing in the over-mature stage. The resource utilization efficiency (uniform angle and forest layer index) showed continuous optimization, reaching optimal spatial configuration in over-mature stands. This study developed a spatial structure evaluation system for Chinese fir plantations by combining UAV data and cloud modeling, elucidating structural characteristics and developmental patterns across different growth stages, thereby providing theoretical foundations and technical support for close-to-nature management and the precision quality improvement of Chinese fir plantations. Full article

This study examined the structural and ecological drivers of burn severity during the March 2025 wildfire in Uiseong County, Republic of Korea, with a focus on developing a predictive framework using the differenced Normalized Burn Ratio (dNBR). Seventeen candidate variables were evaluated, among which the forest type, stand age, tree height, diameter at breast height (DBH), and Normalized Difference Vegetation Index (NDVI) were consistently identified as the most influential predictors. Burn severity increased across all forest types up to the 4th–5th age classes before declining in older stands. Coniferous forests exhibited the highest severity at the 5th age class (mean dNBR = 0.3069), followed by mixed forests (0.2771) and broadleaf forests (0.2194). Structural factors reinforced this pattern, as coniferous and mixed forests recorded maximum severity within the 5–11 m height range, while broadleaf forests showed relatively stable severity across 3–21 m but declined thereafter. In the final prediction model, NDVI emerged as the dominant variable, integrating canopy density, vegetation vigor, and moisture conditions. Notably, NDVI exhibited a positive correlation with burn severity in coniferous stands during this early-spring event, diverging from the generally negative relationship reported in previous studies. This seasonal anomaly underscores the need to interpret NDVI flexibly in relation to the forest type, stand age, and phenological stage. Overall, the model results demonstrate that mid-aged stands with moderate heights and dense canopy cover are the most fire-prone, whereas older, taller stands show reduced susceptibility. By integrating NDVI with structural attributes, this modeling approach provides a scalable tool for the spatial prediction of wildfire severity and supports resilience-based forest management under climate change. Full article

The stand structure of ancient tea tree (Camellia taliensis) communities is critical for maintaining their structural and functional stability. Therefore, this study employed backpack laser scanning (BLS) technology to extract individual tree parameters (diameter at breast height, tree height, relative coordinates, etc.) in seven sample plots (25 m × 25 m each) to analyze their spatial and non-spatial structure characteristics. Firstly, the accuracy of diameter at breast height (DBH) and tree height (TH) estimations using BLS resulted in a root mean square error (RMSE) of 4.247 cm and 2.736 m and a coefficient of determination (R²) of 0.948 and 0.614, respectively. Secondly, in this community, trees exhibited an aggregated spatial distribution (average uniform angle > 0.59), with small differences in DBH among adjacent trees (average dominance > 0.48) and a high proportion of adjacent trees belonging to different species (average mingling > 0.64). Ancient tea trees in the 5–15 cm diameter class face considerable competitive pressure, with values ranging from 14.28 to 179.03. Thirdly, this community exhibits rich species composition (more than 7 families, 8 genera, and 10 species, respectively), strong regeneration capacity (with an inverse J-shaped diameter distribution), uniform species distribution (Pielou evenness index > 0.71), and high species diversity (with a Shannon–Wiener diversity index ranging from 1.65 to 2.47 and a Simpson diversity index ranging from 0.71 to 0.91), and the ancient tea trees maintain a prominent dominant status and important value ranging from 19.36% to 49%. The results indicate that, under the current conditions, the structure and function of this community collectively exhibit relatively stable characteristics. BLS provides a powerful tool for the research and conservation of rare and endangered species. Full article

Specialized research on large trees in Northeast China is rare. To strengthen the understanding of local large trees, a survey of 4055 tree individuals from 75 plots in southeastern Jilin Province was conducted. The individual number and species composition of large trees in the community, as well as large individual standards in diameter at breast height (DBH) and population structures of typical tree species, were analyzed. By setting a DBH ≥ 50 cm as the threshold, 155 individuals across all the recorded trees were determined as large trees in the community, and 32.9% (51/155) of them were national second-class protected plant species in China. By setting the top 5% in DBH of a certain tree species as the threshold of large individuals of that tree species, the large individual criteria of six typical tree species were determined. The proportion of basal area of large trees to all trees was 30.4%, and the mean proportion of basal area of large individuals across the six typical tree species was 23.9% (±4.0%). As for the population characteristics, Abies nephrolepis and Picea jezoensis had large population sizes but relatively thin individuals, Tilia amurensis and Pinus koraiensis had small population sizes but relatively thick individuals, while Betula costata and Larix olgensis had medium population sizes and medium-sized individuals. Full article

Pedunculate oak (Quercus robur L.), an ecologically and economically important tree species has been significantly affected by oak dieback in recent years. Since one of the symptoms of oak dieback is crown defoliation, this research aimed to determine the quantity, quality, average tree value, and wood defects that influence grading in different stages of oak dieback indicated by tree crown defoliation degree. The research was conducted in a 62- and 116-year-old stand of the lowland Croatian forest. In total, 115 pedunculate oak trees were sampled and processed in 983 logs that were analyzed. The prescribed single-entry volume tables underestimate harvesting volume by 5.45% on site A and 6.16% on site B, while the calculation of net harvesting volume underestimates net volume by 0.26% on site A and overestimates net volume on site B by 4.59%. The analysis of wood defect presence showed that insect holes, rot, and covered knots were the main reasons for the degradation of quality class. Dead trees showed a decreased average tree value in DBH classes 32.5–42.5 cm compared to the healthy trees. Based on the findings of this research, tree crown defoliation degree could be used as a timber quality and average tree value indicator. Full article

Old-growth forests are rare in Europe, yet they play a critical role in biodiversity and carbon storage. This study examines the structural dynamics of the Janj old-growth forest in the Dinaric Alps using repeated field measurements from 2011 and 2021 at 39 systematically arranged 12 m radius plots. All trees (DBH ≥ 7.5 cm), regeneration (10 cm height to 7.5 cm DBH), and coarse woody debris (CWD) were assessed. Results revealed that total basal area declined by 3.5 m² ha⁻¹ over the decade, primarily driven by significant reductions in stem density for silver fir (p = 0.001) and Norway spruce (p = 0.001). In contrast, European beech maintained a stable basal area throughout the study period. Moreover, silver fir exhibited a significant increase in mean diameter (p = 0.032) and a pronounced rise in regeneration individuals (t = 3.257, p = 0.002). These findings underscore a gradual compositional shift towards European beech dominance, with conifers facing higher mortality in larger diameter classes. The substantial volume of CWD (463 m³ ha⁻¹) highlights advanced decay dynamics consistent with mature forest conditions. This study emphasizes the value of repeated measurements to capture subtle yet important successional changes in primeval forests, which is essential for conservation planning and sustainable forest management. Full article

Forest growing stock volume (GSV) is a fundamental indicator for assessing the status of forest resources. It reflects forest carbon storage levels and serves as a key metric for evaluating the carbon sequestration capacity of forest ecosystems, thereby playing a crucial role in supporting national “dual-carbon” objectives. Traditional allometric models typically estimate GSV using tree species, diameter at breast height (DBH), and canopy height. However, at larger spatial scales, these models often neglect stand density, resulting in substantial estimation errors in regions characterized by significant density variability. To enhance the accuracy of large-scale GSV estimation, this study incorporates high-resolution, spatially continuous forest structural parameters—including dominant tree species, stand density, canopy height, and DBH—extracted through the synergistic utilization of active (e.g., Sentinel-1 SAR, ICESat-2 photon data) and passive (e.g., Landsat-8 OLI, Sentinel-2 MSI) multi-source remote sensing data. Within an allometric modeling framework, stand density is introduced as an additional explanatory variable. Subsequently, GSV is modeled in a stratified manner according to tree species across distinct ecological zones within Kunming City. The results indicate that: (1) the total estimated GSV of Kunming City in 2020, based on remote sensing imagery and second-class forest inventory data collected in the same year, was 1.01 × 10⁸ m³, which closely aligns with contemporaneous statistical records. The model yielded an R² of 0.727, an RMSE of 537.566 m³, and a MAE of 239.767 m³, indicating a high level of overall accuracy when validated against official ground-based inventory plots organized by provincial and municipal forestry authorities; (2) the incorporation of the dynamic stand density parameter significantly improved model performance, which elevated R² from 0.565 to 0.727 and significantly reduced RMSE. This result confirms that stand density is a critical explanatory factor; and (3) GSV exhibited pronounced spatial heterogeneity across both tree species and administrative regions, underscoring the spatial structural variability of forests within the study area. Full article

With the intensification of global climate change and human activities, coniferous species as the main components of natural forests in the Altay Mountains are facing the challenges of aging and regeneration. This study systematically analyzed structural heterogeneity and regeneration of three coniferous stand groups, Larix sibirica Ledeb. stand group, Abies sibirica Ledeb.-Picea obovata Ledeb.-Larix sibirica mixed stand group, and Picea obovata stand group, respectively, across western, central, and eastern forest areas of the Altay Mountains in Northwest China based on field surveys in 2023. Methodologically, we integrated Kruskal–Wallis/Dunn’s post hoc tests, nonlinear power-law modeling (diameter at breast height (DBH)–age relationships, validated via R², root mean square error (RMSE), and F-tests), static life tables (age class mortality and survival curves), and dynamic indices. Key findings revealed structural divergence: the L. sibirica stand group exhibited dominance of large-diameter trees (>30 cm DBH) with sparse seedlings/saplings and limited regeneration; the mixed stand group was dominated by small DBH individuals (<10 cm), showing young age structures and vigorous regeneration; while the P. obovata stand group displayed uniform DBH/height distributions and slow regeneration capacity. Radial growth rates differed significantly—highest in the mixed stand group (average of 0.315 cm/a), intermediate in the P. obovata stand group (0.216 cm/a), and lowest in the L. sibirica stand group (0.180 cm/a). Age–density trends varied among stand groups: unimodal in the L. sibirica and P. obovata stand groups while declining in the mixed stand group. All stand groups followed a Deevey-II survival curve (constant mortality across ages). The mixed stand group showed the highest growth potential but maximum disturbance risk, the L. sibirica stand group exhibited complex variation with lowest risk probability, while the P. obovata stand group had weaker adaptive capacity. These results underscore the need for differentiated management: promoting L. sibirica regeneration via gap-based interventions, enhancing disturbance resistance in the mixed stand group through structural diversification, and prioritizing P. obovata conservation to maintain ecosystem stability. This multi-method framework bridges stand-scale heterogeneity with demographic mechanisms, offering actionable insights for climate-resilient forestry. Full article

Forest ecosystems play a pivotal role in the global carbon cycle and climate change mitigation. Forest aboveground biomass (AGB), a critical indicator of carbon storage and sequestration capacity, has garnered significant attention in ecological research. Recently, uncrewed aerial vehicle-borne laser scanning (ULS) technology has emerged as a promising tool for rapidly acquiring three-dimensional spatial information on AGB and vegetation carbon storage. This study evaluates the applicability and accuracy of UAV-LiDAR technology in estimating the spatiotemporal dynamics of AGB and vegetation carbon storage in Robinia pseudoacacia (R. pseudoacacia) plantations in the gully regions of the Loess Plateau, China. At the sample plot scale, optimal parameters for individual tree segmentation (ITS) based on the canopy height model (CHM) were determined, and segmentation accuracy was validated. The results showed root mean square error (RMSE) values of 13.17 trees (25.16%) for tree count, 0.40 m (3.57%) for average tree height (AH), and 320.88 kg (16.94%) for AGB. The regression model, which links sample plot AGB with AH and tree count, generated AGB estimates that closely matched the observed AGB values. At the watershed scale, ULS data were used to estimate the AGB and vegetation carbon storage of R. pseudoacacia plantations in the Caijiachuan watershed. The analysis revealed a total of 68,992 trees, with a total carbon storage of 2890.34 Mg and a carbon density of 62.46 Mg ha⁻¹. Low-density forest areas (<1500 trees ha⁻¹) dominated the landscape, accounting for 94.38% of the tree count, 82.62% of the area, and 92.46% of the carbon storage. Analysis of tree-ring data revealed significant variation in the onset of growth decline across different density classes of plantations aged 0–30 years, with higher-density stands exhibiting delayed growth decline compared to lower-density stands. Compared to traditional methods based on diameter at breast height (DBH), carbon storage assessments demonstrated superior accuracy and scientific validity. This study underscores the feasibility and potential of ULS technology for AGB and carbon storage estimation in regions with complex terrain, such as the Loess Plateau. It highlights the importance of accounting for topographic factors to enhance estimation accuracy. The findings provide valuable data support for density management and high-quality development of R. pseudoacacia plantations in the Caijiachuan watershed and present an efficient approach for precise forest carbon sink accounting. Full article

Unpiloted aerial systems (UAS) and light detection and ranging (lidar) sensors provide users with an increasingly accessible mechanism for precision forestry. As these technologies are further adopted, questions arise as to how select processing methods are influencing subsequent high-resolution modelling and analysis. This study addresses how specific individual tree detection (ITD) methods impact the successful detection of trees of varying sizes within complex forests. First, while many studies have compared ITD methods over several sites, algorithms, or sets of parameters based on a singular validation metric, this study quantifies how 10 processing methods perform across varying tree-height size quartiles and varying tree diameter at breast height (dbh) size quartiles. In total, over 1000 reference trees from 20 species within three complex temperate forest sites were analyzed at an average point density of 826.8 ${\mathrm{p}\mathrm{t}\mathrm{s}/\mathrm{m}}^2$. The results indicate that across four tree height size classes, the highest overall F-score (0.7344) was achieved with F-scores ranging from 0.857 for the largest and 0.633 for the smallest height size class. To further expand on this analysis, generalized linear models were used to compare the top performing and worst performing ITD method for each tree size variable and study site along a continuous gradient. This analysis suggests clear distinctions in the performance (true positive and false positive rates) based on tree sizes and ITD method. UAS-lidar users must ensure that demonstrated ITD processing methods are validated in ways that communicate their relative effectiveness for trees of all sizes. Without such consideration, the results of this study show that forest surveys and management conducted using these technologies may not accurately characterize trees present within complex forests. Full article

Riparian forests in the valley area of the Irtysh River Basin are capable of providing a variety of ecosystem services such as water conservation and biodiversity maintenance. Their health condition is an important reflection of their ability to maintain the stability of ecosystem structure and perform ecosystem functions. In this study, a comprehensive survey was conducted to observe the typical distribution areas of riparian forests in the valley of six tributaries and one main stream of the Irtysh River Basin. Twelve indicators were chosen from the three categories of vigor (i.e., productivity), organization (i.e., species diversity and structure complexity), and resistance (i.e., harmful factors and disturbances) to form an evaluation system. Expert-based and statistical weighting were applied to calculate the health scores of riparian forests in the valley and prioritized the health grades of seven rivers. Several criteria were used to further classify the unhealthy level of each river individually. The results of this study can be used as a foundation for future conservation and orderly development of riparian forests in the valley area. The results show that (1) the Kuyertes River was classified as healthy, while the Haba and Berezek Rivers were classified as unhealthy. (2) Among the three evaluation categories, the organization consistently achieved higher scores compared to vigor and resistance. (3) Unhealthy conditions were consistently observed in the midstream sections of each river. (4) Forest types such as Salix alba L. forests, Populus euphratica Oliv. forests, and Betula pendula Roth forests were particularly prone to poor health outcomes. The health of the riparian forests was relatively unsatisfactory due to the conflicting water resource allocation. The protection and restoration of riparian forests in the valley area of the Haba and Berezek Rivers should be prioritized in the future, as well as the middle reaches of each tributary. Additionally, it is necessary to pay attention to three key indicators: stand volume per unit area, stand density, and diameter at breast high (dbh) class structure to improve the health condition of riparian forests. Full article

One of the priorities in European policy is the greater use of wood. In this context, it is important to know the total amount of CO₂ absorbed by the tree and accumulated in the wood. In the timber industry, butt logs are mainly processed. The aim of this study is to analyze diameter at breast height (DBH), wood density (WD), and the amount of CO₂ in grand fir (GF), Douglas fir (DF), northern red oak (NRO), and black locust (BL) wood. The DBH and bark thickness were measured, and cores were taken to study WD and calculate the amount of CO₂. Analyses were conducted in three age classes of trees. It was found that in the youngest age class, DF had a significantly larger DBH compared to NRO and BL, and GF had a significantly larger DBH compared to NRO. The wood density of coniferous species was significantly lower compared to broadleaved species. DF absorbed the most CO₂. In Class III, DF had significantly larger DBH and significantly lower wood density compared to NRO and BL. DF absorbed significantly more CO₂ compared to NRO. In Classes IV and V, DF had larger DBH compared to NRO and lower wood density. The amount of CO₂ absorbed by both species was similar. Taking into account the amount of absorbed CO₂, the durability of the wood, and aspects related to sustainable forest management of the four studied non-native tree species, Douglas fir seems to be the best choice for cultivation in Polish forests. Full article