Tree Location Research Articles

Estimation of Damaged Regions by the Bark Beetle in a Mexican Forest Using UAV Images and Deep Learning

Sustainable forestry for the management of forest resources is more important today than ever before because keeping forests healthy has an impact on human health. Recent advances in Unmanned Aerial Vehicles (UAVs), computer vision, and Deep Learning (DL) models make remote sensing for Forest Insect Pest and Disease (FIPD) possible. In this work, a UAV-based remote sensing process, computer vision, and a Deep Learning framework are used to automatically and efficiently detect and map areas damaged by bark beetles in a Mexican forest located in the Hidalgo State. First, the image dataset of the region of interest (ROI) is acquired by a UAV open hardware platform. To determine healthy trees, we use the tree crown detection prebuilt Deepforest model, and the trees diseased by pests are recognized using YOLOv5. To map the area of the damaged region, we propose a method based on morphological image operations. The system generates a comprehensive report detailing the location of affected zones, the total area of the damaged regions, GPS co-ordinates, and both healthy and damaged tree locations. The overall accuracy rates were 88% and 90%, respectively. The results obtained from a total area of 8.2743 ha revealed that 16.8% of the surface was affected and, of the 455 trees evaluated, 34.95% were damaged. These findings provide evidence of a fast and reliable tool for the early evaluation of bark beetle impact, which could be expanded to other tree and insect species.

Wild chimpanzees remember and revisit concealed, underground army ant nest locations throughout multiple years

Chimpanzees use spatiotemporal cognition for fruit foraging by remembering tree locations and fruiting seasons. However, the spatiotemporal cognition behind exploiting other foods has rarely been studied. Here, we investigate whether chimpanzees use memory to exploit concealed, underground army ant nests. We analyse 679 chimpanzee visits to four nests recorded during five years (2018–2022) using camera traps in a savanna habitat. We explore if chimpanzees intentionally revisit nests, study how they detect ants, and assess ant availability and chimpanzee ant consumption. Nests are concealed, scarce, and intermittently reoccupied, yet chimpanzees eat ants frequently. We find that out of 34 identified chimpanzees who visit the nests, 23 revisit at least one. Chimpanzees visit nest sites significantly more often than similar sites without nests. Individuals revisit significantly sooner and inspect significantly longer nests where they have more recently encountered ants. The apes use sight, smell, taste, touch, and probing tools, to detect ants inside nests. We provide the first evidence suggesting that chimpanzees use spatial and episodic-like memory to exploit concealed social insects throughout multiple years. Our results expand our understanding of the cognitive strategies behind chimpanzee insectivory, suggesting it may have played an important role in the evolution of primate spatiotemporal cognition.

Advancing Forest Plot Surveys: A Comparative Study of Visual vs. LiDAR SLAM Technologies

Forest plot surveys are vital for monitoring forest resource growth, contributing to their sustainable development. The accuracy and efficiency of these surveys are paramount, making technological advancements such as Simultaneous Localization and Mapping (SLAM) crucial. This study investigates the application of SLAM technology, utilizing LiDAR (Light Detection and Ranging) and monocular cameras, to enhance forestry plot surveys. Conducted in three 32 × 32 m plots within the Tibet Autonomous Region of China, the research compares the efficacy of LiDAR-based and visual SLAM algorithms in estimating tree parameters such as diameter at breast height (DBH), tree height, and position, alongside their adaptability to forest environments. The findings revealed that both types of algorithms achieved high precision in DBH estimation, with LiDAR SLAM presenting a root mean square error (RMSE) range of 1.4 to 1.96 cm and visual SLAM showing a slightly higher precision, with an RMSE of 0.72 to 0.85 cm. In terms of tree position accuracy, the three methods can achieve tree location measurements. LiDAR SLAM accurately represents the relative positions of trees, while the traditional and visual SLAM systems exhibit slight positional offsets for individual trees. However, discrepancies arose in tree height estimation accuracy, where visual SLAM exhibited a bias range from −0.55 to 0.19 m and an RMSE of 1.36 to 2.34 m, while LiDAR SLAM had a broader bias range and higher RMSE, especially for trees over 25 m, attributed to scanning angle limitations and branch occlusion. Moreover, the study highlights the comprehensive point cloud data generated by LiDAR SLAM, useful for calculating extensive tree parameters such as volume and carbon storage and Tree Information Modeling (TIM) through digital twin technology. In contrast, the sparser data from visual SLAM limits its use to basic parameter estimation. These insights underscore the effectiveness and precision of SLAM-based approaches in forestry plot surveys while also indicating distinct advantages and suitability of each method to different forest environments. The findings advocate for tailored survey strategies, aligning with specific forest conditions and requirements, enhancing the application of SLAM technology in forestry management and conservation efforts.

Phylogenetic tree instability after taxon addition: empirical frequency, predictability, and consequences for online inference.

Online phylogenetic inference methods add sequentially arriving sequences to an inferred phylogeny without the need to recompute the entire tree from scratch. Some online method implementations exist already, but there remains concern that additional sequences may change the topological relationship among the original set of taxa. We call such a change in tree topology a lack of stability for the inferred tree. In this paper, we analyze the stability of single taxon addition in a Maximum Likelihood framework across 1, 000 empirical datasets. We find that instability occurs in almost 90% of our examples, although observed topological differences do not always reach significance under the AU-test. Changes in tree topology after addition of a taxon rarely occur close to its attachment location, and are more frequently observed in more distant tree locations carrying low bootstrap support. To investigate whether instability is predictable, we hypothesize sources of instability and design summary statistics addressing these hypotheses. Using these summary statistics as input features for machine learning under random forests, we are able to predict instability and can identify the most influential features. In summary, it does not appear that a strict insertion-only online inference method will deliver globally optimal trees, although relaxing insertion strictness by allowing for a small number of final tree rearrangements or accepting slightly suboptimal solutions appears feasible.

Research Note: Multi-Algorithm-Based urban tree information extraction and Its applications in urban planning

Urban trees provide several vital social and environmental services. Within the field of urban planning, tree information is currently usually obtained through expensive and time-consuming fieldwork. This research presents a multi-algorithm methodology that extracts urban tree information, including tree location, absolute height, crown perimeter, and species (group) from airborne laser scanning (ALS) datasets and high-resolution aerial images. We first determine the location of trees from the ALS dataset. After a filtration step removing the erroneous tree locations, we simulate each location’s canopy based on aerial imagery. Finally, we utilize the extracted canopy images to perform tree species classification with deep learning. The validation assessment showed overall good credibility (>70 %) in urban areas and better performance (90 %) in street areas. Compared to other methods that require additional information collection, our methodology uses common data in city databases, enabling cities to collect and update large-scale tree information in a fast manner and supporting decision-makers with important information on understanding the value of urban green under the context of ecosystem services, urban heat islands, and CO2 mitigations.

Impact of urbanization on soapnut Sapindus trifoliatus L. tree cover and the need for community involvement: a case study from Kochi, Kerala, India

ABSTRACT The South Indian soapnut tree, Sapindus trifoliatus L, is a midsized evergreen tree from the Indian subcontinent whose fruit can produce natural detergents, biodiesel, and biopesticides. In this study, we document the systematic destruction of soapnut trees through a citizen-supported tree census in an emerging Tier 2 city, Kochi, in South India. In the study, 3580 respondents allowed us to find and map 210 locations of soapnut trees across 411.57 km2. Kochi expanded suddenly in the early 2000s, with a drastic increase in built-up area (126%) and a steady decline in wetlands (57.6%) and croplands (15%). Habitat loss and removal from home gardens has quartered soapnut tree density, to 0.11 km−2. With only 50 trees remaining, the population of the South Indian soapnut will reach the brink of local extinction by 2080.

GIS-based management of a campus tree inventory for assessing optimal shade tree locations: a case study of National Cheng Kung University, Taiwan

GIS-based management of a campus tree inventory for assessing optimal shade tree locations: a case study of National Cheng Kung University, Taiwan

Spatial organisation of the soil macrofauna community of an oak forest in the steppe zone of Ukraine

Background. Environmental impact assessments and the development of measures for the protection and sustainable use of ecosystems should take into account that not only steppe ecosystems but also forest, marsh, salt marsh and meadow ecosystems are referenced for the steppe zone. A comparative approach requires the study of reference ecosystems to understand how much a particular ecosystem has been transformed or how far it is from natural patterns in the restoration process. The soil macrofaunal community of the forest ecosystem of the right bank of the Samara River can be considered a reference for many forest ecosystems in the region. The aim of this study was to identify patterns of spatial organization of the soil macrofaunal community of an oak forest on the right bank of the Samara River. Materials and Methods. A study was conducted in a deciduous woodland located in an oak forest on the right bank of the Samara River. The study area was divided into 5 transects, each consisting of 20 sampling points with a 2 m distance between rows. The samples of the soil macrofauna were taken from a single block of soil that was 25×25×30 cm deep and removed quickly. Vascular plant species lists were recorded for each 2×2 m subplot. The soil penetration resistance and electrical conductivity were measured. Soil faunal trophic activity was assessed by means of a bait lamina test. Results and Discussion. The spatial structure of the community is complex in terms of hierarchy. The driver of the broad-scale component of spatial variation in the community is the properties of the topsoil, mainly the density of the litter. Vegetation cover forms a broad component of the spatial variation in soil macrofauna. An important factor in structuring ecological space is the location of trees. The pure spatial pattern is represented by broad-, medium-, and fine-scale components. Conclusion. The soil macrofaunal community of an oak forest on the slope of the right bank of a steppe river has a high level of abundance and taxonomic and ecological diversity. The spatial distribution of trees forms a broad-scale component of variation in the soil macrofaunal community, and herbaceous cover forms a medium-scale component. The fine-scale component of community variation is due to neutral factors.

Unruptured intracranial aneurysm volume change patterns and association with age, sex, location in vascular tree, and common risk factors: a single-centre retrospective study.

Unruptured intracranial aneurysms pose a significant clinical and decision-making dilemma. Increase in dome size is one of the crucial indications for treatment. Almost no data exists as to how aneurysms change in size over time. 102 patients (76 women) who had a total of 501 CT examinations were included in the study. Inclusion criteria were: at least three CT angiography studies, an observation period of at least three years, or bleeding during the follow-up period. In each study, the volume of each aneurysm was measured at least four times by two experienced neuroradiologists with the use of dedicated tools. Collected data was used to obtain numerical volume change models for each aneurysm. 149 aneurysms were analysed in the study (118 in women) No significant differences in location, size or age of observation were detected between men and women. Median follow-up was 5.64 years (IQR 4.17-7.71) and total aneurysm observation time amounted to 964.59 years. There were 57 branching zone aneurysms (women 46), 44 sidewall aneurysms (women 36), 20 anterior communicating artery aneurysms (women 16), 20 posterior communicating artery aneurysms (women 13), and eight posterior circulation aneurysms (women 7). 78 (52%) aneurysms remained stable (women 59), 24 (16.6%) increased their volume (women 20), and five (3.4%) decreased (women 4). In 42 (28%) cases, we observed non-uniform routes of volume changes over surveillance (women 35). In the last group, analysing the whole period of follow-up, 29 (69%) did not change volume (women 24), 11 (26%) grew (women 10), and two decreased in size (4.8%, women 1). Bifurcation zone aneurysms, lower aspect ratio, lower patient age, and higher initial volume were associated with an increased risk of aneurysm growth. Posterior circulation aneurysms presented the lowest rate of volume increase. A substantial amount of followed up aneurysms could change volume in a non-uniform way, and an increase in volume may not lead to aneurysm rupture.

Impacts of ash tree removals on summer daytime temperatures in Madison, Wisconsin

Maintaining and increasing canopy cover is frequently promoted as a strategy for mitigating excess heat in cities. However, the impact of changing tree cover on surrounding air temperatures is often unpredictable and can depend on tree species, size, shape, and location. In this study, we explore whether the removal of ash trees in one downtown neighborhood in Madison, Wisconsin affected surrounding air temperatures at small spatial scales (15 to 35 m). We used a bicycle-mounted temperature and radiation sensor to repeatedly record high-frequency observations along four transects. We observed no discernible difference between daytime air temperatures near locations surrounded by tree removals and temperatures at locations without any nearby tree removals. Overall, across the four clusters of streets that were monitored, proximity to mature ash trees did not correlate to reduced air temperatures. Attempts to model temperature as a function of surrounding land cover and street tree characteristics all had poor predictive power (R2 ranged from 0.01 to 0.54), and explanatory variables related to tree cover were never statistically significant. The finding that the removal of ash trees did not impact daytime air temperatures patterns at the neighborhood scale suggests that the most densely developed streets in Madison may not easily support sufficient canopy cover to experience tree-induced cooling, underscoring the importance of pursuing a variety of strategies to mitigate urban warming.

Strategic tree placement for urban cooling: A novel optimisation approach for desired microclimate outcomes

Trees are crucial elements for improving urban microclimates by providing cooling through shading, evapotranspiration, and windbreaks. To maximise their cooling effects, it is essential to strategically position the trees in optimal locations. However, research on optimising tree location and its impact on microclimates is limited owing to computational challenges and costs. This study introduces a novel method that employs three optimisation algorithms—i.e., Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimisation (PSO), and Ant Colony Optimisation (ACO)—to identify the optimal locations for trees in urban environments to enhance urban thermal comfort. The research methodology involves simulating microclimate responses to tree placements optimised by each algorithm and assessing the results based on urban thermal comfort. The results underscore the efficacy of optimised tree locations, demonstrating that optimising tree locations can significantly reduce the Universal Thermal Comfort Index (UTCI) in urban areas. Furthermore, the findings suggest that the clustering of tree canopies has a compounding impact on these cooling benefits in urban areas. Notably, all three algorithms significantly improved UTCI. PSO demonstrated the rapid identification of effective tree configurations. However, ACO provided the most substantial reduction in air temperature, highlighting its potential as an effective tool for urban cooling. While efficient, NSGA-II plateaued earlier, suggesting its utility in scenarios where timely solutions are crucial.

Location and differentiation of chestnut tree (Castanea sativa Mill.) individuals grafted with traditional cultivars using spatio-temporal analysis of remote-sensed imagery, dendro-chronological analysis, and SSR genotyping

Location and differentiation of chestnut tree (<i>Castanea sativa</i> Mill.) individuals grafted with traditional cultivars using spatio-temporal analysis of remote-sensed imagery, dendro-chronological analysis, and SSR genotyping

The Ordered Median Tree Location Problem

In this paper, we propose the Ordered Median Tree Location Problem (OMT). The OMT is a single-allocation facility location problem where p facilities must be placed on a network connected by a non-directed tree. The objective is to minimize the sum of the ordered weighted averaged allocation costs plus the sum of the costs of connecting the facilities in the tree. We present different MILP formulations for the OMT based on properties of the minimum spanning tree problem and the ordered median optimization. Given that ordered median location problems are rather difficult to solve we have improved the OMT solution performance by introducing covering variables in a valid reformulation plus developing two pre-processing phases to reduce the size of this formulations. In addition, we propose a Benders decomposition algorithm to approach the OMT. We establish an empirical comparison between these new formulations and we also provide enhancements that together with a proper formulation allow to solve medium size instances on general random graphs.

Post-Logging Canopy Gap Dynamics and Forest Regeneration Assessed Using Airborne LiDAR Time Series in the Brazilian Amazon with Attribution to Gap Types and Origins

Gaps are openings within tropical forest canopies created by natural or anthropogenic disturbances. Important aspects of gap dynamics that are not well understood include how gaps close over time and their potential for contagiousness, indicating whether the presence of gaps may or may not induce the creation of new gaps. This is especially important when we consider disturbances from selective logging activities in rainforests, which take away large trees of high commercial value and leave behind a forest full of gaps. The goal of this study was to quantify and understand how gaps open and close over time within tropical rainforests using a time series of airborne LiDAR data, attributing observed processes to gap types and origins. For this purpose, the Jamari National Forest located in the Brazilian Amazon was chosen as the study area because of the unique availability of multi-temporal small-footprint airborne LiDAR data covering the time period of 2011–2017 with five data acquisitions, alongside the geolocation of trees that were felled by selective logging activities. We found an increased likelihood of natural new gaps opening closer to pre-existing gaps associated with felled tree locations (&lt;20 m distance) rather than farther away from them, suggesting that small-scale disturbances caused by logging, even at a low intensity, may cause a legacy effect of increased mortality over six years after logging due to gap contagiousness. Moreover, gaps were closed at similar annual rates by vertical and lateral ingrowth (16.7% yr−1) and about 90% of the original gap area was closed at six years post-disturbance. Therefore, the relative contribution of lateral and vertical growth for gap closure was similar when consolidated over time. We highlight that aboveground biomass or carbon density of logged forests can be overestimated if considering only top of the canopy height metrics due to fast lateral ingrowth of neighboring trees, especially in the first two years of regeneration where 26% of gaps were closed solely by lateral ingrowth, which would not translate to 26% of regeneration of forest biomass. Trees inside gaps grew 2.2 times faster (1.5 m yr−1) than trees at the surrounding non-gap canopy (0.7 m yr−1). Our study brings new insights into the processes of both the opening and closure of forest gaps within tropical forests and the importance of considering gap types and origins in this analysis. Moreover, it demonstrates the capability of airborne LiDAR multi-temporal data in effectively characterizing the impacts of forest degradation and subsequent recovery.

Contrasting effects of urban trees on air quality: From the aerodynamic effects in streets to impacts of biogenic emissions in cities

Urban trees are often not considered in air-quality models although they can significantly impact the concentrations of pollutants. Gas and particles can deposit on leaf surfaces, lowering their concentrations, but the tree crown aerodynamic effect is antagonist, limiting the dispersion of pollutants in streets. Furthermore, trees emit Biogenic Volatile Organic Compounds (BVOCs) that react with other compounds to form ozone and secondary organic aerosols. This study aims to quantify the impacts of these three tree effects (dry deposition, aerodynamic effect and BVOC emissions) on air quality from the regional to the street scale over Paris city. Each tree effect is added in the model chain CHIMERE/MUNICH/SSH-aerosol. The tree location and characteristics are determined using the Paris tree inventory, combined with allometric equations. The air-quality simulations are performed over June and July 2022. The results show that the aerodynamic tree effect increases the concentrations of gas and particles emitted in streets, such as NOx (+4.6 % on average in streets with trees and up to +37 % for NO2). This effect increases with the tree Leaf Area Index and it is more important in streets with high traffic, suggesting to limit the planting of trees with large crowns on high-traffic streets. The effect of dry deposition of gas and particles on leaves is very limited, reducing the concentrations of O3 concentrations by −0.6 % on average and at most −2.5 %. Tree biogenic emissions largely increase the isoprene and monoterpene concentrations, bringing the simulated concentrations closer to observations. Over the two-week sensitivity analysis, biogenic emissions induce an increase of O3, organic particles and PM2.5 street concentrations by respectively +1.1, +2.4 and + 0.5 % on average over all streets. This concentration increase may reach locally +3.5, +12.3 and + 2.9 % respectively for O3, organic particles and PM2.5, suggesting to prefer the plantation of low-emitting VOC species in cities.

Vandalism on city trees: a case study from KNUST campus, Ghana

ABSTRACT Tree vandalism has harmful consequences that impact the performance of trees, affecting the flow of their benefits to society. However, questions about the common forms of tree vandalism and factors contributing to a tree’s vulnerability to vandalism have not been well researched. Using the campus of Kwame Nkrumah University of Science and Technology as a case study, the current research identified the common forms of tree vandalism and determined the relationship between these forms and tree species, size, and location. The study area was stratified into three based on land use: Faculty area, Students’ residence, and Lecturers’ residence. Using the Quantum Geographic Information System (QGIS), 100 × 100 m grids were laid on the study area map, and 10% of the grids were randomly selected from each stratum. All trees within the selected grids were identified and assessed. A total of 185 incidents of tree damage were recorded from the 131 trees assessed across the three strata. The highest incidence of damage recorded was broken branches (90), while burnt trees had the lowest frequency of occurrence (6). A total of 61 trees from 19 species were recorded as vandalised according to our classification. Tree size and proximity to the road network did not influence the type of tree vandalism recorded. However, our study suggests that tree vandalism may be location-specific, with trees in highly visible and crowded areas more likely to be vandalised with acts that seek people’s attention, while those in isolated areas are less likely to be vandalised through attention-seeking acts. This study is among the few which has attempted to empirically document a common phenomenon that has received less attention and has been overlooked in several societies.

Tree inventory data from permanent plots in French forest reserves.

We present a data set resulting from the first round of a national monitoring program of forest reserves. It contains 9538 permanent plots, distributed across 111 study sites in mainland France (including Corsica). Notably focusing on dead wood measurement, this protocol has primarily been applied in strict forest reserves and special nature reserves (sensu Bollmann & Braunisch 2013), with 68% (6494) of the plots being currently located in strict forest reserves (unmanaged) and 24.7% (2363 plots) in forests unmanaged for at least 50 years. Sites cover a large variety of ecological conditions, from lowland to subalpine forests, but with an underrepresentation of Mediterranean forests (Table 1). The protocol assesses all the stages of a tree's life cycle, from seedling to decomposed lying dead wood. On each plot, a combination of three sampling techniques was used: (1) fixed-area inventory for regeneration, standing dead trees, living trees, and coarse woody debris (CWD) with diameter over 30 cm; (2) transect lines for CWD with diameter <30 cm; and (3) fixed-angle plot method for living trees with diameter at breast height (DBH) >30 cm (using a relascopic angle of 3%). Measurements include exact tree location (azimuth, distance), species, diameter(s), tree-related microhabitats, decay stage and bark cover, and seedling cover. With ongoing climate change, the program network can also provide important information to monitor changes in forest ecosystems. It can also be used as forest management monitoring or conservation status assessment. These data are freely available for noncommercial scientific use (Creative Commons Attribution 4.0 CC BY SA 4.0) with attribution, and this paper must be cited if this material is reused.

Significant impact of urban tree biogenic emissions on air quality estimated by a bottom-up inventory and chemistry transport modeling

Abstract. Biogenic volatile organic compounds (BVOCs) are emitted by vegetation and react with other compounds to form ozone and secondary organic matter (OM). In regional air quality models, biogenic emissions are often calculated using a plant functional type approach, which depends on the land use category. However, over cities, the land use is urban, so trees and their emissions are not represented. Here, we develop a bottom-up inventory of urban tree biogenic emissions in which the location of trees and their characteristics are derived from the tree database of the Paris city combined with allometric equations. Biogenic emissions are then computed for each tree based on their leaf dry biomass, tree-species-dependent emission factors, and activity factors representing the effects of light and temperature. Emissions are integrated in WRF-CHIMERE air quality simulations performed over June–July 2022. Over Paris city, the urban tree emissions have a significant impact on OM, inducing an average increase in the OM of about 5 %, reaching 14 % locally during the heatwaves. Ozone concentrations increase by 1.0 % on average and by 2.4 % during heatwaves, with a local increase of up to 6 %. The concentration increase remains spatially localized over Paris, extending to the Paris suburbs in the case of ozone during heatwaves. The inclusion of urban tree emissions improves the estimation of OM concentrations compared to in situ measurements, but they are still underestimated as trees are still missing from the inventory. OM concentrations are sensitive to terpene emissions, highlighting the importance of favoring urban tree species with low-terpene emissions.

3DFin: a software for automated 3D forest inventories from terrestrial point clouds

Abstract Accurate and efficient forest inventories are essential for effective forest management and conservation. The advent of ground-based remote sensing has revolutionized the data acquisition process, enabling detailed and precise 3D measurements of forested areas. Several algorithms and methods have been developed in the last years to automatically derive tree metrics from such terrestrial/ground-based point clouds. However, few attempts have been made to make these automatic tree metrics algorithms accessible to wider audiences by producing software solutions that implement these methods. To fill this major gap, we have developed 3DFin, a novel free software program designed for user-friendly, automatic forest inventories using ground-based point clouds. 3DFin empowers users to automatically compute key forest inventory parameters, including tree Total Height, Diameter at Breast Height (DBH), and tree location. To enhance its user-friendliness, the program is open-access, cross-platform, and available as a plugin in CloudCompare and QGIS as well as a standalone in Windows. 3DFin capabilities have been tested with Terrestrial Laser Scanning, Mobile Laser Scanning, and terrestrial photogrammetric point clouds from public repositories across different forest conditions, achieving nearly full completeness and correctness in tree mapping and highly accurate DBH estimations (root mean squared error &amp;lt;2 cm, bias &amp;lt;1 cm) in most scenarios. In these tests, 3DFin demonstrated remarkable efficiency, with processing times ranging from 2 to 7 min per plot. The software is freely available at: https://github.com/3DFin/3DFin.

Comparing Deep Learning and MCWST Approaches for Individual Tree Crown Segmentation

Abstract. Accurate segmentation of individual tree crowns (ITC) segmentation is essential for investigating tree-level based growth trends and assessing tree vitality. ITC segmentation using remote sensing data faces challenges due to crown heterogeneity, overlapping crowns and data quality. Currently, both classical and deep learning methods have been employed for crown detection and segmentation. However, the effectiveness of deep learning based approaches is limited by the need for high-quality annotated datasets. Benefiting from the BaKIM project, a high-quality annotated dataset can be provided and tested with a Mask Region-based Convolutional Neural Network (Mask R-CNN). In addition, we have used the deep learning based approach to detect the tree locations thus refining the previous Marker controlled Watershed Transformation (MCWST) segmentation approach. The experimental results show that the Mask R-CNN model exhibits better model performance and less time cost compared to the MCWST algorithm for ITC segmentation. In summary, the proposed framework can achieve robust and fast ITC segmentation, which has the potential to support various forest applications such as tree vitality estimation.