Tree Crown Research Articles

Harvester Efficiency During Thinning Operations in Alder Planted Stands with Some of Coppice Origin

In Central European conditions, harvester use becomes more popular for broadleaved tree species, though there are still some difficulties with effective delimbing of satisfactory quality. Considering these issues, economic aspects are ultimately crucial when deciding on the use of harvesters and assessing the effectiveness of their productivity. The objective of the present research was to apply different harvesters in thinning of alder stands to determine their productivity level focusing on the use of tree trunk for logs. The study was carried out in alder stands under thinning where five different harvesters were used in nine stands, five of which were of coppice origin. Additionally, in six cases, harvesting was done after the growing season and in three cases during the growing season, when trees were covered with leaves. An average productivity was 14.42 m3 PMH0-1, with maximum values of 24.34 m3 PMH0-1 in a coppice stand, and 23.66 m3 PMH0-1 in a planted stand. Delimbing was carried out in the tree crowns with the mean diameter as small as 7.9 cm under bark, which shows very good use of the tree trunk for logs. It was also established that the thicker the tree, the bigger the top diameter of the last log, leading to bigger biomass production, e.g. for energy purposes, but also with smaller effectiveness of log processing.

The ISPRS International Contest on Individual Tree Crown Segmentation using High-Resolution Images and the Initial Findings

Abstract. Tree canopy plays an essential role in the biophysical activities in forest environment. During the past two decades, individual tree delineation using high-resolution imagery data has become a hot topic in forest sensing research. Individual Tree Crown (ITC) segmentation methods aim to generate masks that delineating the boundary of each ITC, which supports various tree parameter extractions. Thanks to the rapid development of deep learning, the ITC segmentation methods achieved remarkable improvement. However, existing research suffers from the limited availability of the datasets, and the lack of evaluation standards as well as task-orientated neural networks. In 2024, the International Society of Photogrammetry and Remote Sensing (ISPRS) launched the first International Contest of ITC Segmentation. The contest aims to reveal the state-of-the-art of the ITC method development using high-resolution images, to clarify the remaining barriers and challenges, and to guide further explorations in the field. This paper overviews the contest and reports the initial finding regarding the impact factors of the method performance.

The influence of tree species on small scale spatial soil properties and microbial activities in a mixed bamboo and broad-leaved forest

Soil enzyme activity and microbial biomass play a critical role in myriad ecological processes. Bamboo and broad-leaved mixed forests have received widespread attention as important forestry models for ecological restoration and sustainable development; however, our understanding the influences of broad-leaved tree species in mixed bamboo forests on soil properties and microbial activity remains unclear. Here we sampled twenty-seven spatially interspersed stands of bamboo-Castanopsis chinensis Hance mixed forest (CCB), bamboo-Alniphyllum fortune (Hemsl.) Makino mixed forest (AFB), and bamboo-Choerospondias axillaris mixed forest (CAB), with different mixing ratios (0–10 %, 10–20 %, 20–40 % canopy proportions) in subtropical China, to examine the effects of tree species and mixed ratio on soil nutrients, microbial biomass, and enzyme activity. We found that the different forests exhibited variations in soil nutrient levels. CAB forests exhibit notably higher mean C, N, and P contents than AFB and CCB, particularly at a 10–20 % mixing ratio where SOC concentration reached 46.50 g/kg. CAB forests demonstrated significantly higher activities of invertase (mean 701.83U/g), urease (8393.44U/g), and catalase (501.73U/g) compared to AFB and CCB forests, with peak enzyme activities observed at a 10–20 % mixing ratio. Soil microbial biomass C and N were notably greater in CAB and CCB forests than in AFB forests. CAB forests also exhibited the highest soil microbial biomass P (mean 48.68 mg/kg), which rose consistently with an increased mixing ratio. Multiple factor analysis revealed that the enzyme activities were significantly correlated with the annual growth of fine roots in the forest and were positively correlated with resident C, total N, total P, C: N, and C: P. Overall, the results provide insights into the importance of tree species and crown size in bamboo and broadleaved tree mixed forest in soil features and the microbial activity while providing management guidance for the selection of mixed tree species for sustainable management of bamboo forest soil microenvironment.

Decoupling of Tree‐Ring Cellulose δ18O and δ2H Highlighted by Their Contrasting Relationships to Climate and Tree Intrinsic Variables

ABSTRACTOxygen (δ18O) and hydrogen (δ2H) stable isotope ratios are tightly coupled in precipitation and, albeit damped, in leaf water, but are often decoupled in tree‐ring cellulose. The environmental and physiological conditions in which this decoupling occurs are not yet well understood. We investigated the relationships between δ18O and δ2H and tree‐ring width (TRW), tree crown volume, tree age and climate in silver fir and Douglas‐fir and found substantial differences between δ18O and δ2H. Overall, δ18O–δ2H correlations were weak to absent but became significantly negative under high summer vapour pressure deficit (VPD). δ18O and δ2H had positive and negative nonlinear relationships with TRW, respectively, with clear relationships at the site and tree levels for silver fir and, to a lesser extent, for Douglas‐fir. Age trends for silver fir were weakly negative in δ18O but positive in δ2H. Tree crown volume and δ18O or δ2H had no significant relationships. Most strikingly, δ18O strongly depended on spring climate (precipitation and VPD), whereas δ2H depended on summer climate (temperature and VPD) for both species. Our study shows that the δ18O–δ2H decoupling in tree‐ring cellulose in two temperate conifer species could be highlighted by their contrasting relationships to climate and tree intrinsic variables (TRW, age).

Groundcover improves nutrition and growth of citrus trees and reduces water runoff, soil erosion and nutrient loss on sloping farmland

IntroductionGroundcover management plays a crucial role in improving water retention and soil nutrition in orchard systems, thereby preventing environmental constrains by non-point source pollution. However, effectiveness of groundcover management in citrus orchards developed on sloping farmland with eroded purple soil has not been studied in detail. In particular, information on the soil nutrient losses, e.g., nitrogen (N) and phosphorus (P), through interflow and its effects on growth and nutrition of citrus plants has not been reported.MethodsThe present study evaluated the effects of different cover crops, i.e., Lolium perenne L. (Lolium), Vicia villosa Roth (Vicia) and Orychophragmus violaceus (Ory), on nutrition and growth of citrus trees as well as water, soil and nutrient retention in an orchard developed in sloping farmland during two consecutive years.Results and discussionThe results show that the groundcover species Lolium and Vicia mediated nursing effects on nutrition and growth of citrus trees. These nursing effects included enhanced foliar levels of carbon(C), N and P as well as increased tree height, stem diameter, and crown width. Groundcover management generally reduced the annual surface runoff, interflow, soil loss, total N loss and total P loss. Among the cover crop species studied, Lolium and Vicia were overall more efficient than Ory in this context. Lolium reduced the average annual total loss of N and P by 42.53% and 49.23%, respectively, compared with clean tillage. The estimated annual reduction potentials of soil, N and P losses in Southwestern China were 16.3, 3.4 and 8.5 million tons yr-1, respectively. Obviously, Lolium and Vicia provide highly beneficial ground coverage on sloping farmland and, thus, can be used for future sustainable development of citrus orchards.

Spatiotemporal diversity of bacterial endophyte microbiome of mandarin (Citrus reticulata) in the northern Persian Gulf and its HCN production and N2 fixation.

Endophytes are symbionts that live in healthy plants and potentially improve the health of plant holobionts. Here, we investigated the bacterial endophyte community of Citrus reticulata grown in the northern Persian Gulf. Bacteria were isolated seasonally from healthy trees (root, stem, bark, trunk, leaf, and crown tissues) in four regions of Hormozgan province (i.e., Ahmadi, Siyahoo, Sikhoran, Roudan), a subtropical hot region in Iran. A total of 742 strains from 17 taxa, 3 phyla, and 5 orders were found, most of which belonged to Actinobacteria (Actinobacteriales) as the dominant group, followed by Firmicutes (Bacillales), Proteobacteria (Sphingomonadales, Rhizobiales), and Cyanobacteria (Synechoccales). The genera included Altererythrobacter, Arthrobacter, Bacillus, Cellulosimicrobium, Curtobacterium, Kocuria, Kytococcus, Methylopila, Mycobacterium, Nocardioides, Okiabacterium, Paracraurococcus, and Psychrobacillus. The most frequently occurring species included Psychrobacillus psychrodurans, Kytococcus schroetri, and Bacillus cereus. In addition, the overall colonization frequency and variability of endophytes were higher on the trunks. The leaves showed the lowest species variability in all sampling periods. The frequency of endophyte colonization was also higher in summer. The Shannon-Wiener (H') and Simpson indices varied with all factors, i.e., region, season, and tissue type, with the maximum in Roudan. Furthermore, 52.9% of the strains were capable of nitrogen fixation, and 70% produced antagonistic hydrogen cyanide (HCN). Thus, C. reticulata harbors a variety of bioactive bacterial endophytes that could be beneficial for host fitness in such harsh environments.

Integration of weighted majority voting in machine learning algorithms to enhance pine tree crown mapping on UAV imagery

Abstract. The shape and area of the crown of each tree are among the most influential parameters for identifying and controlling the processes of photosynthesis, respiration, transpiration and its management. In such a way that various physiographic functions, such as carbon dioxide absorption, light energy absorption, oxygen release and transpiration, which are vital for the growth and development of the tree, are done in the crown. In this research, the RGB image of the UAV with a spatial resolution of 2 cm was resampled to three pixel sizes of 10, 30 and 50 cm. Then, each image was classified separately by SVM, ANN and MLC algorithms, which are all part of Ensemble. In the next step, each of the obtained crowns was compared with the digitization of the same crown, and based on the area of the crown obtained from each classification and normalization method, the weight was obtained specifically for the same crown. Finally, by using the weighted majority voting method, classifications were fusioned at the decision level. The results showed that the ANN method gives better results in all pixel sizes compared to MLC and SVM. Also, the combination of different classification methods with the weighted majority voting method based on the weight assigned to the same crown based on each classification method has significantly increased the classification accuracy of the tree crown in all the sizes of the analyzed pixels.

Tree crowns broken off by windstorms are an unstable life raft for Collembola

There are a number of ways to clear the aftermath of a windthrow disturbance of forest stands, the most common practice being to remove all broken trees and broken-off crowns lying on the ground. This practice leads to complete exposure of the soil, which deprives soil invertebrates (including Collembola) of the protection of trees that affords them a chance of surviving. Accordingly, following a windthrow disturbance of pine stands in 2017, a three-year study of collembolan assemblages was undertaken in stands spared from salvage logging. We aimed to test the effect of three different levels of disturbance (severely, moderately and least disturbed stands with a canopy cover of 0–20%, 20–60% and 60–90%, respectively) on the survival of Collembola assemblages and to determine its association with changes in the soil environment and in the LAI index. Additionally, in the severely and moderately disturbed stands, Collembola were sampled between crowns of fallen trees and under the crowns. There were no significant differences in density, species richness and proportions of individuals of belowground “soil” and aboveground “epedaphic” species between the Collembolan assemblages that were associated with the degree of windthrow disturbance and time since disturbance. The study confirmed the presence of a significantly higher number of species and proportion of “epedaphic” species, and a lower proportion of “soil” species in the assemblages sampled under fallen tree crowns than between crowns. Analysis of principal response curves (PRC) yielded unexpected results as it indicated that these differences were significant only in the first year post-disturbance, thus suggesting a very short-lasting protective effect of tree crowns on Collembola, RDA analysis with preselected factors from environmental variables of interest (LAI of standing and fallen tree crowns, soil respiration, soil temperature and humidity, soil pH and soil nitrogen and carbon content) indicated the LAI index as significant for the Collembolan assemblages in the first yearpost-disturbance, soil moisture in the second year, and soil temperature in the third year. This sequence of significant indices over a three year period is compatible with the fallen crowns becoming more and more thinned as a result of needles falling off (from shade to full exposure to sunlight). We nevertheless postulate that at least some trees or their crowns lying on the ground should be left in place during clearance of windthrow-affected tree stands to facilitate restoration of the soil biota.

Tree Trimming Effects on 3-Dimensional Crown Structure and Tree Biomechanics: A Pilot Project

AbstractBackgroundAlong electric distribution corridors in urban-exurban landscapes, forest edges are susceptible to damage associated with storm events. Disturbances and management interventions designed to preempt their effects (e.g., tree trimming) alter characteristics of tree structure and morphology (e.g., branch and crown structure), which may be associated with tree failure and likelihood of associated infrastructure damage. This study assessed the relationship between 3-dimensional tree crown structure and tree biomechanics and characterized the effect of utility tree trimming on tree sway dynamics using terrestrial laser scanning (TLS).MethodsIn this study we extracted and analyzed measures of crown structure (i.e., crown asymmetry, crown area, total volume, crown diameter to height ratio, and crown evenness) for individual trees during leaf-off conditions before and after implementation of tree trimming and linked these measures to tree biomechanics data, to evaluate how commonly implemented trimming practices affect both tree sway frequency and displacement—important indicators of tree stability.ResultsResults illustrated the effects of common tree trimming practices on tree crown structure, but there were not consistent changes to tree movement characteristics directly following tree trimming across our 24 study trees. However, we found that the associated changes in crown structure through tree trimming affected tree displacement in moderate wind conditions. Additionally, we found there were no significant differences between frequencies across treatment types.ConclusionsThis pilot project lays the foundation for understanding the intricate relationship between 3-dimensional crown structure and tree biomechanics following roadside tree trimming.

Extreme climatic events, biotic interactions and species-specific responses drive tree crown defoliation and mortality in Italian forests

Extreme climatic events, biotic interactions and species-specific responses drive tree crown defoliation and mortality in Italian forests

Individual Tree Crown Detection and Classification of Live and Dead Trees Using a Mask Region-Based Convolutional Neural Network (Mask R-CNN)

Mapping the distribution of living and dead trees in forests, particularly in ecologically fragile areas where forests serve as crucial ecological environments, is essential for assessing forest health, carbon storage capacity, and biodiversity. Convolutional neural networks, including Mask R-CNN, can assist in rapid and accurate forest monitoring. In this study, Mask R-CNN was employed to detect the crowns of Casuarina equisetifolia and to distinguish between live and dead trees in the Pingtan Comprehensive Pilot Zone, Fujian, China. High-resolution images of five plots were obtained using a multispectral Unmanned Aerial Vehicle. Six band combinations and derivatives, RGB, RGB-digital surface model (DSM), Multispectral, Multispectral-DSM, Vegetation Index, and Vegetation-Index-DSM, were used for tree crown detection and classification of live and dead trees. Five-fold cross-validation was employed to divide the manually annotated dataset of 21,800 live trees and 7157 dead trees into training and validation sets, which were used for training and validating the Mask R-CNN models. The results demonstrate that the RGB band combination achieved the most effective detection performance for live trees (average F1 score = 74.75%, IoU = 70.85%). The RGB–DSM combination exhibited the highest accuracy for dead trees (average F1 score = 71.16%, IoU = 68.28%). The detection performance for dead trees was lower than for live trees, which may be due to the similar spectral features across the images and the similarity of dead trees to the background, resulting in false identification. For the simultaneous detection of living and dead trees, the RGB combination produced the most promising results (average F1 score = 74.18%, IoU = 69.8%). It demonstrates that the Mask R-CNN model can achieve promising results for the detection of live and dead trees. Our study could provide forest managers with detailed information on the forest condition, which has the potential to improve forest management.

Benchmarking of Individual Tree Segmentation Methods in Mediterranean Forest Based on Point Clouds from Unmanned Aerial Vehicle Imagery and Low-Density Airborne Laser Scanning

Three raster-based (RB) and one point cloud-based (PCB) algorithms were tested to segment individual Aleppo pine trees and extract their tree height (H) and crown diameter (CD) using two types of point clouds generated from two different techniques: (1) Low-Density (≈1.5 points/m2) Airborne Laser Scanning (LD-ALS) and (2) photogrammetry based on high-resolution unmanned aerial vehicle (UAV) images. Through intensive experiments, it was concluded that the tested RB algorithms performed best in the case of UAV point clouds (F1-score > 80.57%, H Pearson’s r > 0.97, and CD Pearson´s r > 0.73), while the PCB algorithm yielded the best results when working with LD-ALS point clouds (F1-score = 89.51%, H Pearson´s r = 0.94, and CD Pearson´s r = 0.57). The best set of algorithm parameters was applied to all plots, i.e., it was not optimized for each plot, in order to develop an automatic pipeline for mapping large areas of Mediterranean forests. In this case, tree detection and height estimation showed good results for both UAV and LD-ALS (F1-score > 85% and >76%, and H Pearson´s r > 0.96 and >0.93, respectively). However, very poor results were found when estimating crown diameter (CD Pearson´s r around 0.20 for both approaches).

Determination of forest canopy cover of different sized stands with diverse structure using ALS data: case study of the Białowieża Forest (Poland)

ABSTRACT The need for objective methods to determine tree canopy cover (CC) across large numbers of stands has led to the development of techniques that utilise airborne laser scanning (ALS) data, which provides a reproducible and detailed representation of canopy geometry. We developed a method for determining CC area and evaluated the estimation accuracy for stands of different sizes, structure and composition. This method is based on tree crown geometries obtained from ALS data, and verified with field measurements using data for 3245 stands of the Białowieża Forest District in Poland. In relatively large stands (3–5 ha), the theoretical error of prediction decreased from 0.13 to 0.10 with increasing stand area. In stands larger than 10 ha, however, the error in estimating CC was less than ±0.10. Although every estimation method comes with its own assumptions and errors, the presented method eliminates the subjectivity in observer bias prevalent in traditional field-based ocular assessments and provides a more transparent and methodologically uniform approach for estimating CC in forests.

Automated tree crown labeling with 3D radiative transfer modelling achieves human comparable performances for tree segmentation in semi-arid landscapes

Mapping tree crowns in arid or semi-arid areas, which cover around one-third of the Earth’s land surface, is a key methodology towards sustainable management of trees. Recent advances in deep learning have shown promising results for tree crown segmentation. However, a large amount of manually labeled data is still required. We here propose a novel method to delineate tree crowns from high resolution satellite imagery using deep learning trained with automatically generated labels from 3D radiative transfer modeling, intending to reduce human annotation significantly. The methodological steps consist of 1) simulating images with a 3D radiative transfer model, 2) image style transfer learning based on generative adversarial network (GAN) and 3) tree crown segmentation using U-net segmentation model. The delineation performances of the proposed method have been evaluated on a manually annotated dataset consisting of more than 40,000 tree crowns. Our approach, which relies solely on synthetic images, demonstrates high segmentation accuracy, with an F1 score exceeding 0.77 and an Intersection over Union (IoU) above 0.64. Particularly, it achieves impressive accuracy in extracting crown areas (r2 greater than 0.87) and crown densities (r2 greater than 0.72), comparable to that of a trained dataset with human annotations only. In this study, we demonstrated that the integration of a 3D radiative transfer model and GANs for automatically generating training labels can achieve performances comparable to human labeling, and can significantly reduce the time needed for manual labeling in remote sensing segmentation applications.

I want to climb to the tops of trees! Factors facilitating the development of ivy vines in central European forests

Abstract Lianas, which are considered to form tree-related microhabitats, are known as important elements of tropical forests; however, their ecological function and relationships with host trees (phorophytes) in temperate forests are poorly known. This gap in knowledge stems from a low species diversity and abundance of lianas in temperate forests. An exception is common ivy (Hedera helix), which is widely distributed and is currently increasing its abundance in temperate forests. In this study, we examined the relationships between ivy vines with features of their phorophytes, using Central European upland mixed forests as an example. We assess the presence and density of ivy within 69 study plots, established in the forest interior and ecotone. We use generalized linear mixed-effects models to assess drivers of ivy’s presence and its density, while accounting for the tree diameter at breast height, bark roughness, and the canopy light transmittance. We show that ivy is able to grow on nearly all tree species, although it prefers phorophytes with rough bark and a large diameter. Large generative individuals (ivy vines that produce fruits) were found mostly on veteran trees (usually oaks, alders, or pines). For its growth, ivy requires tree phorophytes with only a moderate transparency of light through the tree crowns, which is likely related to evergreen leaves that enable ivy vines to also develop during leaf-off periods. The features of phorophytes preferred by ivy indicate that the vine finds optimal conditions for development in old patches of tree stand, often in areas inaccessible or unprofitable for forest management. We propose using large and fruiting ivy vines as indicators of old-growth forests that deserve protection, which would be in line with the current policy of sustaining and restoring close-to-natural forests in Europe.

Distribution and Abundance of Pine Needle Aphids (Eulachnus rileyi Williams) and Their Potential Natural Enemies on Pine Tree Species (Pinus patula and Pinus elliottii) at Sao Hill Forest Plantation, Tanzania

A study was conducted at SHFP, Tanzania to assess the distribution and abundance of PNA and their potential natural enemies. Systematic sampling was used to select every 5th tree along the row of the particular compartment. Five shoots were randomly cut from lower, middle and upper crown parts of each selected tree for laboratory analysis. Data analysis was performed using R and Excel, with normality and homogeneity of variance checked using Shapiro-Wilk and Levene’s tests, respectively. Results revealed that PNA was un-equally distributed throughout the divisions, trees species and age classes at SHFP. The abundance of adult aphids per twig was 7.6 and 12.9 for Division II and III, respectively and was significantly different. Similarly, the mean abundance of eggs and nymphs per twig were 5.5 and 12.2 in Division II and 9.2 and 21.1 in Division III, respectively. Nymphs were more abundant than eggs and adults, while eggs were the least abundant across all examined pine species and age classes. The abundance of adult aphid was 19.6 and 7.0 for P. elliottii and P. patula, respectively and was significantly different. For P. patula, the abundance of adult aphid per twig was 7.3, 8.5 and 5.1 for young, middle and old age classes respectively. In P. elliottii stands, the abundance of adult aphid population per twig was 23.2 and 17.9 for middle and old age classes respectively. The middle part of the tree crown had the highest aphid abundance for both tree species and age classes. Three main natural enemies were identified: Coccinellid beetles (Coleoptera: Coccinellidae), Spiders (Arachnida) and Stink bugs (Pentatomidae), but their numbers were low. The correlation between the abundance of PNA and natural enemies was weakly positive (Rho = 0.0859) but statistically significant (p = 0.035). Tending operations i.e. thinning, weeding, pruning, and regular insect survey and monitoring programs, are recommended to mitigate favorable conditions for aphid growth. Additionally, the SHFP management team should reconsider the introduction and release of Tetraphleps raoi or other predators as biological control agents over large area to increase the current stock of the natural enemies as there were no introduce natural enemies found in the plantation

An Intermittent Fertilization Control System for Fruit Tree Crown Detection

In light of the current dearth of strip intermittent fertilization devices in standardized orchards, this study presents the design of an intermittent fertilization control system based on fruit tree crown detection, developed with the objective of meeting the agronomic requirements of strip furrow fertilization in standardized orchards. The initial stage of the process entails the design of the essential components of the fertilization apparatus, followed by the construction of the intermittent fertilization control system. The ultrasonic sensor was employed as the fruit tree crown detection module, and a mathematical model of fertilization speed was constructed to achieve uniform intermittent fertilization. Furthermore, in order to enhance the responsiveness and reliability of the fertilization servo motor, MATLAB Simulink was employed to assess the dynamic performance of the system under disparate control strategies. Ultimately, to validate the simulation outcomes, a field trial was conducted to assess the precision and uniformity of intermittent fertilization. The results demonstrate that the dynamic performance of the system under the fuzzy PID control strategy is optimal, and the coefficient of variation of the fertilizer uniformity of the intermittent fertilization device is less than 7%. The mean effective fertilization rate exceeded 85%, with the primary indices satisfying the agronomic criteria.

Individual Tree Crown Delineation Using Airborne LiDAR Data and Aerial Imagery in the Taiga–Tundra Ecotone

The circumpolar Taiga–Tundra Ecotone significantly influences the feedback mechanism of global climate change. Achieving large-scale individual tree crown (ITC) extraction in the transition zone is crucial for estimating vegetation biomass in the transition zone and studying plants’ response to climate change. This study employed aerial images and airborne LiDAR data covering several typical transitional zone regions in northern Finland to explore the ITC delineation method based on deep learning. First, this study developed an improved multi-scale ITC delineation method to enable the semi-automatic assembly of the ITC sample collection. This approach led to the creation of an individual tree dataset containing over 20,000 trees in the transitional zone. Then, this study explored the ITC delineation method using the Mask R-CNN model. The accuracies of the Mask R-CNN model were compared with two traditional ITC delineation methods: the improved multi-scale ITC delineation method and the local maxima clustering method based on point cloud distribution. For trees with a height greater than 1.3 m, the Mask R-CNN model achieved an overall recall rate (Ar) of 96.60%. Compared to the two conventional ITC delineation methods, the Ar of Mask R-CNN showed an increase of 1.99 and 5.52 points in percentage, respectively, indicating that the Mask R-CNN model can significantly improve the accuracy of ITC delineation. These results highlight the potential of Mask R-CNN in extracting low trees with relatively small crowns in transitional zones using high-resolution aerial imagery and low-density airborne point cloud data for the first time.

Conceptualization and First Realization Steps for a Multi-Camera System to Capture Tree Streamlining in Wind

Forests and trees provide a variety of essential ecosystem services. Maintaining them is becoming increasingly important, as global and regional climate change is already leading to major changes in the structure and composition of forests. To minimize the negative effects of storm damage risk, the tree and stand characteristics on which the storm damage risk depends must be known. Previous work in this field has consisted of tree-pulling tests and targets attached to selected branches. They fail, however, since the mass of such targets is very high compared to the mass of the branches, causing the targets to influence the tree’s response significantly, and because they cannot model dynamic wind loads. We, therefore, installed a multi-camera system consisting of nine cameras that are mounted on four masts surrounding a tree. With those cameras acquiring images at a rate of 10 Hz, we use photogrammetry and a semi-automatic feature-matching workflow to deduce a 3D model of the tree crown over time. Together with motion sensors mounted on the tree and tree-pulling tests, we intended to learn more about the wind-induced tree response of all dominant aerial tree parts, including the crown, under real wind conditions, as well as dampening processes in tree motion.

Improving AGB estimations by integrating tree height and crown radius from multisource remote sensing.

Precise estimation of forest above ground biomass (AGB) is essential for assessing its ecological functions and determining forest carbon stocks. It is difficult to directly obtain diameter at breast height (DBH) based on remote sensing imagery. Therefore, it is crucial to accurately estimate the AGB with features extracted directly from RS. This paper demonstrates the feasibility of estimating AGB from crown radius (R) and tree height (H) features extracted from multi-source RS data. Accurate information on tree height (H), crown radius (R), and diameter at breast height (DBH) can be obtained through point clouds generated by airborne laser scanning (ALS) and terrestrial laser scanning (TLS), respectively. Nine allometric growth equations were used to fit coniferous forests (Larix principis-rupprechtii) and broadleaf forests (Fraxinus chinensis and Sophora japonica). The fitting performance of models constructed using only "H" or "R" was compared with that of models constructed using both combined. The results showed that the quadratic polynomial model constructed with "H+R" fitted the AGB estimation better in each vegetation type, especially in the scenario of mixed tall and short coniferous forests, in which the R2 and RMSE were 0.9282 and 25.30 kg (rRMSE 17.31%), respectively. Therefore, using high-resolution data to extract crown radius and tree height can achieve high-precision, global-scale estimation of forest above ground biomass.