Use Of Terrestrial Laser Scanning Research Articles

Побудова твердотілої моделі історичного об’єкту: на прикладі форту «Марушка Ліс»

Purpose of this work is to use terrestrial laser scanning for analysis and construction of a digital model of the fort “Marushka Lis” focusing on the process of data collection, processing, and their further use, particularly for web mapping of post-military sites. In the modern world, the preservation and restoration of historical structures is an important task that requires the application of advanced technologies. Methodology. Terrestrial laser scanning serves as an indispensable tool in this process, providing accurate and detailed spatial data. A technological scheme for creating a digital model of a historical object has been proposed. The study of historical objects using various methods of information collection was considered, namely: topographic surveying, terrestrial digital photogrammetry, terrestrial laser scanning, ground-penetrating radar studies, tachymetric surveying, GNSS. The methodology for creating a digital model of a historical object and the presented technological scheme, which includes data collection, processing of the obtained results, and output data, are described. Results. A comprehensive approach was applied to create the model, which included studying the history of the object, terrestrial laser scanning, terrestrial digital photogrammetry, and conducting geodetic measurements. A key aspect was the accurate and detailed reproduction of all architectural and structural elements of the fort. The use of software such as Leica Cyclone REGISTER 360, Autodesk ReCap, and Autodesk Revit allowed the integration of collected data into one accurate and detailed model. The sequential execution of work according to the proposed methodology enabled the creation of a digital model of the fort “Marushka Lis.” Scientific novelty and practical significance. The scientific novelty lies in the use of terrestrial laser scanning and 3D modeling for the reconstruction of a destroyed post-military object. The obtained digital model of the fort “Marushka Lis” will be used in web mapping of post-military sites in Lviv region.

Intricacies of Opening Geometry Detection in Terrestrial Laser Scanning: An Analysis Using Point Cloud Data from BLK360

This study investigates the use of terrestrial laser scanning (TLS) in urban excavation sites, focusing on enhancing ground deformation detection by precisely identifying opening geometries, such as gaps between pavement blocks. The accuracy of TLS data, affected by equipment specifications, environmental conditions, and scanning geometry, is closely examined, especially with regard to the detection of openings between blocks. The experimental setup, employing the BLK360 scanner, aimed to mimic real-world paving situations with varied opening widths, allowing an in-depth analysis of how factors related to scan geometry, such as incidence angles and opening orientations, influence detection capabilities. Our examination of various factors and detection levels reveals the importance of the opening width and orientation in identifying block openings. We discovered the crucial role of the opening width, where larger openings facilitate detection in 2D cross-sections. The overall density of the point cloud was more significant than localized variations. Among geometric factors, the orientation of the local object geometry was more impactful than the incidence angle. Increasing the number of laser beam points within an opening did not necessarily improve detection, but beams crossing the secondary edge were vital. Our findings highlight that larger openings and greater overall point cloud densities markedly improve detection levels, whereas the orientation of local geometry is more critical than the incidence angle. The study also discusses the limitations of using a single BLK360 scanner and the subtle effects of scanning geometry on data accuracy, providing a thorough understanding of the factors that influence TLS data accuracy and reliability in monitoring urban excavations.

Comparison of two novel methods for counting wheat ears in the field with terrestrial LiDAR

BackgroundThe metrics for assessing the yield of crops in the field include the number of ears per unit area, the grain number per ear, and the thousand-grain weight. Typically, the ear number per unit area contributes the most to the yield. However, calculation of the ear number tends to rely on traditional manual counting, which is inefficient, labour intensive, inaccurate, and lacking in objectivity. In this study, two novel extraction algorithms for the estimation of the wheat ear number were developed based on the use of terrestrial laser scanning (TLS) in conjunction with the density-based spatial clustering (DBSC) algorithm based on the normal and the voxel-based regional growth (VBRG) algorithm. The DBSC involves two steps: (1) segmentation of the point clouds using differences in the normal vectors and (2) clustering of the segmented point clouds using a density clustering algorithm to calculate the ear number. The VBRG involves three steps: (1) voxelization of the point clouds, (2) construction of the topological relationships between the voxels as a connected region using the k-dimensional tree, and (3) detection of the wheat ears in the connected areas using a regional growth algorithm.ResultsThe results demonstrated that DBSC and VBRG were promising in estimating the number of ears for different cultivars, planting densities, N fertilization rates, and growth stages of wheat (RMSE = 76 ~ 114 ears/m2, rRMSE = 18.62 ~ 27.96%, r = 0.76 ~ 0.84). Comparing the performance of the two algorithms, the overall accuracy of the DBSC (RMSE = 76 ears/m2, rRMSE = 18.62%, r = 0.84) was better than that of the VBRG (RMSE = 114 ears/m2, rRMSE = 27.96%, r = 0.76). It was found that with the DBSC, the calculation in points as units permitted more detailed information to be retained, and this method was more suitable for estimation of the wheat ear number in the field.ConclusionsThe algorithms adopted in this study provide new approaches for non-destructive measurement and efficient acquisition of the ear number in the assessment of the wheat yield phenotype.

Horizontal viewsheds of large herbivores as a function of woodland structure

AbstractThere is great potential for the use of terrestrial laser scanning (TLS) to quantify aspects of habitat structure in the study of animal ecology and behaviour. Viewsheds—the area visible from a given position—influence an animal's perception of risk and ability to respond to potential danger. The management and conservation of large herbivores and their habitats can benefit greatly from understanding how vegetation structure shapes viewsheds and influences animal activity patterns and foraging behaviour. This study aimed to identify how woodland understory structure influenced horizontal viewsheds at deer eye height. Mobile TLS was used in August 2020 to quantify horizontal visibility—in the form of Viewshed Coefficients (VC)—and understory leaf area index (LAI) of 71 circular sample plots (15‐m radius) across 10 woodland sites in North Wales (UK) where fallow deer (Dama dama) are present. The plots were also surveyed in summer for woody plant size structure, stem density and bramble (Rubus fruticosus agg.). Eight plots were re‐scanned twice in winter to compare seasonal VC values and assess scan consistency. Sample plots with higher densities of small stems had significantly reduced VC 1 m from the ground. Other stem size classes, mean percentage bramble cover and understory LAI did not significantly affect VC. There was no difference in VC between summer and winter scans, or between repeated winter scans. The density of small stems influenced viewsheds at deer eye height and may alter behavioural responses to perceived risk. This study demonstrates how TLS technology can be applied to address questions in large herbivore ecology and conservation.

An instructional workflow for using terrestrial laser scanning (TLS) to quantify vegetation structure for wildlife studies

Vegetation structure is a crucial component of habitat suitability for wildlife, but methods traditionally used to quantify it can be costly, subjective, or difficult to replicate. There have been substantial advancements, and growing interest, in the use of terrestrial laser scanning (TLS) methods to measure fine-scale vegetation attributes in ecological research, but limited opportunities for ecologists and practitioners to learn how to incorporate these into applied research. Here, we provide a starting point for those who want to incorporate TLS methods into ecological research and monitoring, using a case study from a temperate forest in South-Eastern Australia. We scanned 24 sites at different stages of post-fire recovery as part of a larger project measuring the impact of fire on forest dwelling bats, using a FARO Focus 3DS. Using the data from these scans, we present an example workflow with accompanying R code to demonstrate how to process the point clouds and extract a range of vegetation structure metrics relevant to habitat structure for wildlife, including vegetation height, cover, density, and heterogeneity. We discuss how three-dimensional data obtained through TLS can be valuable to wildlife studies and opens up the potential to explore advanced ecological and conservation questions around how vegetation structure influences wildlife behaviours, distribution patterns, and responses to disturbance.

Using terrestrial laser scanning to evaluate non-destructive aboveground biomass allometries in diverse Northern California forests

A crucial part of carbon accounting is quantifying a tree’s aboveground biomass (AGB) using allometric equations, but species-specific equations are limited because data to inform these equations requires destructive harvesting of many trees which is difficult and time-consuming. Here, we used terrestrial laser scanning (TLS) to non-destructively estimate AGB for 282 trees from 5 species at 3 locations in Northern California using stem and branch volume estimates from quantitative structure models (QSMs) and wood density from the literature. We then compared TLS QSM estimates of AGB with published allometric equations and used TLS-based AGB, diameter at breast height (DBH), and height to derive new species-specific allometric AGB equations for our study species. To validate the use of TLS, we used traditional forestry approaches to collect DBH (n = 550) and height (n = 291) data on individual trees. TLS-based DBH and height were not significantly different from field inventory data (R2 = 0.98 for DBH, R2 = 0.95 for height). Across all species, AGB calculated from TLS QSM volumes were approximately 30% greater than AGB estimates using published Forest Service’s Forest Inventory and Analysis Program equations, and TLS QSM AGB estimates were 10% greater than AGB calculated with existing equations, although this variation was species-dependent. In particular, TLS AGB estimates for Quercus agrifolia and Sequoia sempervirens differed the most from AGB estimates calculated using published equations. New allometric equations created using TLS data with DBH and height performed better than equations that only included DBH and matched most closely with AGB estimates generated from QSMs. Our results support the use of TLS as a method to rapidly estimate height, DBH, and AGB of multiple trees at a plot-level when species are identified and wood density is known. In addition, the creation of new TLS-based non-destructive allometric equations for our 5 study species may have important applications and implications for carbon quantification over larger spatial scales, especially since our equations estimated greater AGB than previous approaches.

Study on the LAI Single Tree Model Based on Terrestrial Laser Scanning

Leaf area index (LAI) is a key parameter for studying global terrestrial ecology and environment and has great ecological significance. How to accurately measure and calculate structural parameters of trees has become an urgent matter. This paper reports the use of terrestrial laser scanning (TLS) as a measurement tool to achieve accurate LAI estimation through point cloud preprocessing measures, the LeWos algorithm, and voxel methods. The accuracy and feasibility of this indirect measurement method were explored. It is found that the single wood structure parameters extracted from TLS have a good linear relationship with manual measurement, and the extraction errors meet the requirements of real-scene conversion. The study also found when the voxel size is consistent with the minimum distance of the point cloud set by TLS instrument, it has a strong correlation with the measured value of canopy analyser. These results lay the foundation for conveniently and quickly obtaining structural parameters of trees, tree growth state detection, and canopy ecological benefit assessment.

Use of UAS and TLS technology in 3D modeling of constructions with complex architecture

3D building models are widely used in many applications. The use of terrestrial laser scanning and UAS photogrammetry for 3D modelling is a popular practice especially for constructions with complex architecture. The present article presents an example of using these technologies successfully for 3D modelling of the Episcopal Cathedral of the Holy Trinity from Baia Mare, Romania.  A number of 51 control and verification points were determined by the closed circuit travel method and the intersection method. All measurements were processed in Terramodel software. The control points used in the georeferencing of the scans were materialized by metal stakes and the verification points were materialized by reflective targets. Depending on the construction configuration, the field of view and the minimum/maximum scanning distances were subsequently set. A total of 45 scans were performed to model the entire cathedral. The photogrammetric flight was performed in RTK mode, with corrections being transmitted from the DJI D-RTK-2 Mobile Station base to the RTK drone. All retrieved frames had geolocation and frame orientation elements recorded by the IMU module. A total number of 222 photograms were taken, as a result of a double grid photogrammetric flight, with the camera oriented at 60 degrees, but also as a result of manual acquisition by performing orbital flights at different heights: an orbital flight on the ground floor, an orbital flight at the level of about 40 meters and an orbital flight around the tower.

Capturing seasonal radial growth of boreal trees with terrestrial laser scanning

Detailed observation techniques are needed to reveal the underlying eco-physiological mechanisms driving tree growth processes. Terrestrial laser scanning (TLS) has proven to be a feasible technique for characterizing trees, but it has still remained unclear whether TLS point clouds and the existing point cloud processing methods can be used for capturing even the smallest signs of the growth process of individual trees. The aim of this study was to investigate the capacity of TLS in observing seasonal radial growth of boreal trees. The experimental setup included 91 sample trees from 20 sample plots characterized with multi-scan TLS point clouds pre- and post-growing season. The sample trees were equipped with dendrometers that provided reference measurements for the increment in diameter at the breast height (Δdbh) that varied from −1.4 mm to 4.0 mm with a mean of 1.0 mm. The experiment confirmed challenges related to quantification of millimeter-level increments in dbh using TLS but cautiously highlighted its feasibility for radial tree growth monitoring when the magnitude of Δdbh exceeds several millimeters and when the aim is to characterize sample plot mean rather than individual tree growth. While the capacity of TLS to characterize Δdbh of individual trees remained rather low (r = 0.17, p = 0.07), the TLS-based estimates for sample plot mean Δdbh were slightly better in line with dendrometer measurements (r = 0.46, p = 0.04). At an individual tree level, the capacity of TLS to determine the occurrence of radial tree growth seemed to be dependent on the magnitude of observed Δdbh and benefit from the analysis of paired diameter measurements along the stem for determining individual tree growth. The results showed overall classification accuracies of a) 60.7 % and b) 70.6 % for the use of TLS in determining whether radial growth had occurred or not when the analysis was based on a) Δdbh measurements only or b) statistically significant mean increment in paired diameter measurements along the stem, respectively. Using the Δdbh-based method, the overall accuracy improved from 56.3 % to 73.0 % when the magnitude of observed Δdbh increased from ≤ 1 mm to > 1 mm, as was expected. Altogether, this study contributes by demonstrating that with TLS data acquisition and existing point cloud processing methods, it is possible to observe seasonal increments in tree structures, which emphasizes the feasibility of TLS in regular monitoring of structural changes even in boreal forest ecosystems.

3D integration of orthophoto mapping and Terrestrial Laser Scanning of the ground surface and underground caverns

Obtaining three-dimensional data for the surface and underground cavities is a complex task that includes using scanning systems to collect accurate data, as well as their processing. In recent years, Unmanned Aerial Systems (UAS) have been very successfully used for capturing geospatial data for ground surface and orthophoto mapping. On the other hand, the use of UAS for underground scanning is a difficult task due to the limited spaces, the lack of GNSS coverage and the low level of illumination in underground terrains. In this regard, the use of Terrestrial Laser Scanning (TLS) is crucial. This work looks for intersection between these two types of scanning systems (UAS as a system for scanning the earth’s surface and LiDAR as a system for scanning underground surfaces) considered in the context of studying cavities and the ground surface above them as well as the possibilities for integration of data obtained from them.

Laser Scanning Investigation and Geophysical Monitoring to Characterise Cultural Heritage Current State and Threat by Traffic-Induce Vibrations: The Villa Farnesina in Rome

A multidisciplinary approach is often the only way to assess the state of the cultural heritage, thus involving different specialist expertise and techniques. The paper shows the paired use of terrestrial laser scanning (TLS) and geophysical monitoring (GM) to detect past effects and analyse the actual vibration levels induced by traffic on cultural heritage. The case study is the Villa Farnesina, one of the most important Renaissance buildings commissioned by the banker Agostino Chigi. The Villa contains frescoes attributed to Raphael and other famous 16th century artists, and it is located a few meters from the Lungotevere, which is one of the busiest roads in the historic centre of Rome. Testimonies report the damages caused by the construction of the embankment of the Tiber River, as well as by the traffic in the second half of the 20th century, so much so as to require requalification of the road artery. The TLS survey allows for detecting cracks and deteriorations of the frescoes, although these were subjected to restoration activities over the time, whereas the (GM) allows analysing actual vibrations induced by traffic at the different floors and outside the Villa. Although the measured vibration limits, as velocity peaks in defined frequency ranges, are below the thresholds established by international codes, the importance of the wall paintings and their already-shown susceptibility to damage suggest keeping the building under constant monitoring.

Effect of Terrestrial Laser Scanning (TLS) parameters on the accuracy of crack measurement in building materials

Terrestrial Laser Scanners (TLS) have gained momentum in identifying cracks and deformations. Although TLS efficiency has been recognized over time, the scan data quality is contingent upon various parameters (e.g., material type and scan settings), which impacts the use of TLS. To address this barrier, this study investigates the measurement accuracy in the context of crack analysis in foam board and common building materials (concrete, wood, and masonry) by conducting a set of controlled experiments with different scan settings (e.g., scan distance and angle of incidence). The findings of this study provide practical contributions to using TLS for crack identification, specifically addressing the effect of different parameters on point cloud data quality and proposing boundary ranges for different scan settings regarding different building materials and crack widths to facilitate TLS planning.

Tree species classification from complex laser scanning data in Mediterranean forests using deep learning

Abstract Recent advances in terrestrial laser scanning (TLS) technology have enabled the automatic capture of three‐dimensional vegetation structure at high resolution, but the scalability of using these data for large‐scale forest monitoring is limited by reliance on intensive manual data processing, including the use of stem maps generated in the field to determine tree species. New methods from data science have the capacity to automate this identification process, reducing the hurdles towards automated inventories with TLS. In particular, contemporary developments in point cloud processing methods, alongside large increases in the computing power of consumer‐level graphics processing units, provide new opportunities. Here, we apply a deep learning‐based approach, based on joint classification from multiple viewpoints for each stem, to automatically classify tree species directly from laser scanning data obtained in structurally complex Mediterranean forests. We also explore the use of data augmentation techniques to maximise performance for a fixed number of manually labelled stems. Our method does not require expensive pre‐processing such as leaf‐wood separation or quantitative reconstructions. Using modern network architectures and data augmentation techniques, and without extensive pre‐processing, we are able to achieve high overall and per‐species accuracy that is comparable or higher than in existing work while using data from a water‐limited ecosystem complicated by structural convergence and multi‐stem trees. Our findings demonstrate the power of deep learning to remove a major TLS data processing obstacle—individual species identification—and to minimise the bottleneck created by manual data labelling requirements in the use of TLS for standard forest monitoring.

Combined use of Terrestrial Laser Scanning and UAV Photogrammetry in producing the LoD3 of 3D high building model

Both Unmanned Aerial Vehicles (UAVs) and Terrestrial Laser Scanners (TLS) are important techniques for surveying and mapping. UAV equipment is commonly used to collect 2D or 3D data acquisition. Meanwhile, TLS equipment is used for obtaining only 3D data acquisition. However, if both are integrated, they were able to produce more accurate data. Multi-sensor data fusion helps overcome the limitations of a single sensor and enables a complete 3D model for the structure and better object classification. This study focuses on studying the combination of UAV and TLS technologies to collect, process data, and create the complete point cloud between two point clouds of the high building in Ha Long city, Quang Ninh province to establish a 3D model at LoD 3 detail level, with high accuracy. FARO FOCUS3D X130 and DJI Phantom 4 RTK equipments were used to acquire the data in the field. The aerial and ground data were processed using FARO SCENE 2019 and Agisoft PhotoScan software, respectively. The data integration process is done by converting both point clouds into the same coordinate system and then by aligning the same points of both points clouds in Cloud Compare. The result of this study is a 3D model at LoD 3 detail level of the high building based on the point cloud accuracy in centimeter level. The combined use of UAV and TLS technologies has proven to be possible to create a highly accurate 3D model, at the 1:500 scale of urban areas according to current standards.

LiSurveying: A high-resolution TLS-LiDAR benchmark

Outdoor point-cloud object localization is an essential processing step for urban scene analysis and modeling in numerous applications, especially in land surveying and site analysis. Given the increasingly use of Terrestrial Laser Scanning (TLS) and LiDAR 3D data acquisition, numerous annotated point-cloud datasets are available and can be used to evaluate computer vision and machine learning based algorithms. Nevertheless, current point-cloud datasets mainly focus on object detection and classification in autonomous driving or urban planning type of applications, and share redundant object classes, e.g., trees, vehicles and pedestrians, which limit their usefulness for land surveying and site analysis. This paper introduces a novel 3D benchmark dataset LiSurveying, which is a large-scale point-cloud dataset with over a billion points and uncommon urban object categories in complex outdoor environments. Our dataset incorporates more urban object classes than existing datasets. Its instances have diverse point densities, shapes and dimensions, which also impose a challenge for point-cloud detection and classification algorithms. We conducted baselines experiments for point-cloud classification using machine learning classifiers and deep learning methods on different subsets of the LiSurveying dataset, and we are able to demonstrate that the various types of object classes, number of instances per class, distribution of object points, and variety of complex scenes, make this LiSurveying benchmark dataset suitable for evaluating 3D point-cloud classification, semantic segmentation, and object detection algorithms.

Terrestrial Laser Scanning: An Operational Tool for Fuel Hazard Mapping?

Fuel hazard estimates are vital for the prediction of fire behaviour and planning fuel treatment activities. Previous literature has highlighted the potential of Terrestrial Laser Scanning (TLS) to be used to assess fuel properties. However, operational uptake of these systems has been limited due to a lack of a sampling approach that balances efficiency and data efficacy. This study aims to assess whether an operational approach utilising Terrestrial Laser Scanning (TLS) to capture fuel information over an area commensurate with current fuel hazard assessment protocols implemented in South-Eastern Australia is feasible. TLS data were captured over various plots in South-Eastern Australia, utilising both low- and high-cost TLS sensors. Results indicate that both scanners provided similar overall representation of the ground, vertical distribution of vegetation and fuel hazard estimates. The analysis of fuel information contained within individual scans clipped to 4 m showed similar results to that of the fully co-registered plot (cover estimates of near-surface vegetation were within 10%, elevated vegetation within 15%, and height estimates of near-surface and elevated strata within 0.05 cm). This study recommends that, to capture a plot in an operational environment (balancing efficiency and data completeness), a sufficient number of non-overlapping individual scans can provide reliable estimates of fuel information at the near-surface and elevated strata, without the need for co-registration in the case study environments. The use of TLS within the rigid structure provided by current fuel observation protocols provides incremental benefit to the measurement of fuel hazard. Future research should leverage the full capability of TLS data and combine it with moisture estimates to gain a full realisation of the fuel hazard.

Digitization of two urban archaeological areas in Reggio Calabria (Italy): Roman Thermae and Greek fortifications

The digitization of Heritage represents a great challenge that Italy is facing in order to improve the state of documentation, conservation, enhancement and dissemination of its huge cultural assets. This paper, part of the project Circuito delle Aree Archeologiche Urbane di Reggio Calabria (a collaboration between the Municipality of Reggio Calabria and the CNR-IPCF of Messina), shows the complete workflow (from field survey to web-sharing) carried out for the enhancement of two archaeological sites located in the urban center of Reggio Calabria. The study-cases selected are represented by the Roman Thermae and the Greek fortification, both located along the Falcomatà waterfront. The metric surveys have been based on the use of terrestrial laser scanning and close-range photogrammetry, well-established techniques for the production of graphic documentation and 3D digital replicas of artifacts ranging from architectural up to object scale. The final outcome of our action is the implementation of a web-based platform (built up with Faro WebShare Cloud) where expert and non-expert users (e.g. scholars, professionals, administrators, tourists) can navigate image-based and 3D point-cloud models and, in addition, search metadata of their specific interest (media, old pictures, results of analyses etc.). This product, absolutely unprecedented and singular for a southern Italy Municipality, more than an interactive museum, is configured as an integrated and partecipative tool capable of improving the state of knowledge, conservation, valorization and dissemination of these sites and their environments. Because of its singularity, this solution can be also considered as a case-study for the evaluation of long-term effects on the growth of tourism, inclusivity and accessibility of cultural places during particular situations (maintenance works, pandemic emergency etc.).

Operationalizing the use of TLS in forest inventories: The R package FORTLS

Terrestrial Laser Scanning (TLS) devices show great potential for application in Forest Inventories (FIs) as they are capable of registering high resolution point clouds rapidly and automatically. Nevertheless, operational use of TLS for FI purposes has been hampered by the absence of algorithms for processing the acquired data, particularly in the single-scan mode, as occlusions result in loss of information. The R package FORTLS has been developed to overcome this obstacle, as it automates the processing of single-scan TLS point cloud data for forestry purposes and includes several features that deal with occlusions. FORTLS makes use of the main advantage of the single-scan scenario in FI, thus improving the efficiency of data acquisition and post-processing. All of these features of the FORTLS package are potentially valuable for the operational use of TLS in FIs, in combination with inference techniques derived from model-based and model-assisted approaches.

Assessment of defoliation and subsequent growth losses caused by Lymantria dispar using terrestrial laser scanning (TLS)

Key messageTLS scans of three surveys before, during and after gypsy moth gradation, allowed high-resolution tracking of defoliation and subsequent inter-annual growth losses on an individual tree level.Foliation strongly determines all tree growth processes but can be reduced by various stress factors. Insect defoliation starts at variable times and is one stress factor that may affect photosynthetic processes and cause immediate reactions like refoliation, which are difficult to detect by surveys repeated at 1-year intervals. This study used a large-scale field experiment in German oak/mixed forests affected by gypsy moths (Lymantria dispar) to test the use of terrestrial laser scanning (TLS) for detecting inter-annual foliation and growth losses at the individual tree level caused by the gypsy moth. The experiment comprised two levels of gypsy moth defoliation risk, high (H) and low (L), as well as two pest control treatment levels: spraying with the insecticide Mimic (M) or unsprayed control (C). The factorial design consisted of four treatment combinations (HC, HM, LC, and LM), applied to 11 spatial blocks with a total of 44 plots. The TLS approach detected the defoliation caused by the gypsy moth, estimated as leaf area and crown perforation parameters. For the first time, TLS-derived tree foliation was evaluated based on inter-annual stem growth. Leaf area and crown perforation showed a correlation of + 0.6 and – 0.35, respectively, with basal area increments. Furthermore, this study revealed subsequent growth losses in the same year due to defoliation. Our results show that TLS can offer new opportunities to develop new indicators that monitor foliation at the individual tree level. The crown perforation can describe defoliation or the tree’s vitality based on one scanning campaign, whereas the leaf area needed at least two.

Measuring tree growth using terrestrial laser scanning

Forests are dynamic ecosystems that are constantly changing. The most common natural reasons for change in forests are the growth and death of trees, as well as the damage occurring to them. Tree growth appears as an increment of its structural dimensions, such as stem diameter, height, and crown volume, which all affect the structure of a tree. Repeated measurements of tree characteristics enable observations of the respective increments indicating tree growth. According to current knowledge, the tree growth process follows the priority theory, where trees aim to achieve sufficient lightning conditions for the tree crown through primary growth, whereas increment in diameter results from the secondary growth. Tree growth is known to have an effect on the carbon sequestration potential of trees as well as on the quality of timber. To improve the understanding of the underlying cause–effect relations driving tree growth, methods to quantify structural changes in trees and forests are needed. The use of terrestrial laser scanning (TLS) has emerged during the recent decade as an effective tool to determine attributes of individual trees. However, the capacity of TLS point cloud-based methods to measure tree growth remains unexplored. This thesis aimed at developing new methods to measure tree growth in boreal forest conditions by utilizing two-date TLS point clouds. The point clouds were also used to investigate how trees allocate their growth and how the stem form of trees develops, to deepen the understanding of tree growth processes under different conditions and over the life cycle of a tree. The capability of the developed methods was examined during a five- to nine-year monitoring period with two separate datasets consisting of 1315 trees in total. Study I demonstrated the feasibility of TLS point clouds for measuring tree growth in boreal forests. In studies II and III, an automated point cloud-based method was further developed and tested for measuring tree growth. The used method could detect trees from two-date point clouds, with the detected trees representing 84.5% of total basal area. In general, statistically significant changes in the examined attributes, such as diameter at breast height, tree height, stem volume, and logwood volume, were detected during the monitoring periods. Tree growth and stem volume allocation seemed to be more similar for trees growing in similar structural conditions. The findings obtained in this thesis demonstrate the capabilities of repeatedly acquired TLS point clouds to be used for measuring the growth of trees and for characterizing the structural changes in forests. This thesis showed that TLS point cloud-based methods can be used for enhancing the knowledge of how trees allocate their growth, and thus help discover the underlying reasons for processes driving changes in forests, which could generate benefits for ecological or silvicultural applications where information on tree growth and forest structural changes is needed.