Search Results (239)

Geometric monitoring of slender support structures, particularly steel lattice transmission towers, is a critical component of power infrastructure diagnostics. Such structures are susceptible to environmental influences and long-term deformation processes, which necessitates precise assessment of their geometric axis. The aim of this study was to evaluate the influence of the terrestrial laser scanning (TLS) scanner class and point cloud registration strategy on the determination of the geometric axis of a steel high-voltage lattice transmission tower (hereafter LTT). Unlike previous studies focused primarily on TLS-based axis reconstruction, this work introduces a comparative assessment of registration strategies, an error propagation model, and the proposed Axis Drift Index (ADI) as quantitative indicators of axis stability. The analysis was based on data obtained using a tachymetric method (reference), a compact scanner (Leica BLK360), and a survey-grade scanner (Riegl VZ-400i). The comparison included planimetric axis deviation, consistency of deformation direction, variation in results with height, and the influence of registration quality. The results show that TLS measurements performed using a survey-grade scanner and target-based registration exhibit high agreement with tachymetric results. In contrast, cloud-to-cloud registration without a stable reference framework leads to cumulative errors and instability of the reconstructed axis, particularly in the upper parts of the structure. The observed deviations in the BLK360 dataset were dominated by registration-related geometric instability rather than unequivocal structural deformation signals. The findings indicate that the accuracy of geometric axis determination in slender structures is governed more by the adopted point cloud registration strategy than by the scanner class itself. The proposed ADI parameter and linear error propagation model additionally enabled a quantitative assessment of geometric consistency with height. From an engineering perspective, this highlights the importance of stable reference systems and appropriate survey design in high-precision TLS applications. Although the study was conducted on a single lattice tower, the results provide practical insight into the reliability of TLS workflows for slender structures characterized by discontinuous geometry and high sensitivity to registration errors. Full article

Deformation monitoring of bridges is essential to ensure the structural integrity and serviceability of these critical civil infrastructures. In this context, geodetic measurements using total stations and 3D terrestrial laser scanning (TLS) surveys can provide accurate and reliable data. Multitemporal geodetic observations from total stations enable the tracking of displacements at discrete points, whereas TLS surveys allow for the extension of deformation analysis to entire surfaces. Both techniques can achieve comparable millimeter-level precision. These methods were applied to monitor the deformation of the Ponte della Costituzione (PdC), the most recent pedestrian arch bridge spanning the Grand Canal in Venice (Italy). A total station was used to measure the displacements of six control points installed on structurally significant locations of the bridge. Between 3 October 2023 and 2 February 2026, 28 multitemporal measurement campaigns were conducted. In addition, four TLS surveys, using two different laser scanners, were carried out on 1 August 2025 and 2 February 2026, in order to capture conditions corresponding to maximum annual thermal deformation. The results derived from geodetic measurements reveal a strong correlation among: (i) variations in the distance between the abutments (on the order of 6–7 mm); (ii) vertical displacements of the central upper points of the arch (ranging from 9 to 12 cm); and (iii) fluctuations in ambient temperature. TLS data highlighted a spatially homogeneous deformation pattern extending from the crown of the arch to the abutments, demonstrating that longitudinal displacements affect the entire lateral structure. Mid-term deformation analysis over the two-year period from 6 February 2024 to 2 February 2026 indicates displacement rates of approximately 1.4 mm/year for increasing separation between the abutments and 16.2 mm/year for the decrease in elevation of the central arch point. However, these trends are significantly influenced by environmental temperature variations, as evidenced by an estimated temperature change rate of −3.5 °C/year over the same period. Therefore, continued deformation monitoring of the PdC bridge is recommended in the coming years, particularly in light of ongoing climate change and the associated increase in temperature variability. Full article

Cross-domain semantic classification of 3D point clouds remains challenging due to strong domain shifts between heterogeneous sensing modalities. Most existing classification frameworks are domain-specific, limiting their use in integrated land–water mapping applications. This study evaluates the transferability of classical geometric machine learning classifiers between terrestrial and underwater point cloud domains without target-domain retraining. Experiments were conducted using terrestrial data acquired with a Leica BLK360 terrestrial laser scanner (TLS) and underwater point clouds collected with a Blueview BV5000 mechanical scanning sonar (MSS). Two dimensionality-based frameworks, CANUPO–Support Vector Machine (SVM) and 3DMASC–Random Forest (RF), were implemented in CloudCompare and assessed under intra-domain and cross-domain configurations. Strong intra-domain performance was achieved, with terrestrial–terrestrial accuracies of 0.99 for CANUPO–SVM and 0.97 for 3DMASC. In underwater evaluation, CANUPO maintained high accuracy (0.97), whereas 3DMASC decreased to 0.86 due to increased variability in the submerged data. Under cross-domain transfer, CANUPO achieved 0.93 accuracy for terrestrial-to-underwater and 0.89 for underwater-to-terrestrial classification, while 3DMASC demonstrated stable generalisation with 0.95 accuracy in both directions. Overall, dimensionality-based geometric descriptors capture stable structural cues across sensing environments, providing an interpretable and efficient pathway for applications such as hydrographic surveying, coastal monitoring, and underwater search-and-rescue detection. Future work will extend validation to larger datasets and explore domain adaptation strategies to further reduce cross-modality domain shift. Full article

This work presents a simulation-based approach to support the planning of Terrestrial Laser Scanning (TLS) surveys for landslide monitoring. Starting from an approximate digital model of the slope, the method estimates the spatial distribution of positional error induced by scanner characteristics, laser beam divergence and, critically, by the incidence angle between the laser beam and the local surface normal. Because complex morphologies cause rapid local variations in incidence angle, neighbouring points may exhibit markedly different error magnitudes, making a direct classification of raw error values insufficient to delineate homogeneous areas. To address this, a multidimensional variable is defined for each simulated point, combining position, estimated error, distance from the scanner and incidence angle. After dimensionality reduction through PCA, the dataset is clustered using K-means with a sufficiently large number of clusters to preserve spatial resolution. Each cluster is associated with a representative error level, and clusters are then merged into broader error classes that delineate zones of comparable expected precision. The procedure is repeated for alternative scanner positions, enabling a comparative evaluation of achievable accuracy across the slope and the identification of areas requiring multiple scans. The method provides a quantitative, reproducible framework to guide TLS station selection and optimize survey design in complex morphological settings. Full article

Accurate and efficient forest inventory methods are crucial for monitoring forest ecosystems, assessing carbon stocks, and supporting sustainable forest management. Traditional field-based techniques, which rely on manual measurements such as diameter at breast height (DBH) and tree height (TH), remain labour-intensive and time-consuming. In this study, we introduce and validate a fully open-source, low-cost terrestrial laser scanning system (LCA-TLS) built from commercially available components and based on the Livox Avia sensor. With a total cost of €2050, the system responds to recent technological developments that have significantly reduced hardware expenses while retaining high data quality. This trend has created new opportunities for broadening access to high-resolution 3D data in ecological research. The performance of the LCA-TLS was assessed under controlled and field conditions and benchmarked against three reference devices: the RIEGL VZ-1000 terrestrial laser scanner, the Stonex X120GO handheld mobile laser scanner, and the iPhone 15 Pro Max structured-light device. The LCA-TLS achieved high accuracy for estimating DBH (RMSE: 1.50 cm) and TH (RMSE: 0.99 m), outperforming the iPhone and yielding results statistically comparable to the Stonex X120GO (DBH RMSE: 1.32 cm; p > 0.05), despite the latter being roughly ten times more expensive. While the RIEGL system produced the most accurate measurements, its cost exceeded that of the LCA-TLS by a factor of about 30. The hardware design, control software, and processing workflow of the LCA-TLS are fully open-source, allowing users worldwide to build, modify, and apply the system with minimal resources. The proposed solution thus represents a practical, cost-effective, and accessible alternative for 3D forest inventory and LiDAR-based ecosystem monitoring. Full article

In this paper, the combined use of Ground Penetrating Radar (GPR) and a Terrestrial Laser Scanner (TLS) is illustrated to highlight multiple advantages arising from the integration of these two distinct Non-Destructive Testing (NDT) techniques in the investigation of a historical wall. In particular, thanks to the TLS point cloud, a precise evaluation of the medium’s thickness, as well as its irregularities, was carried out. Based on this accurate geometrical constraint, a first-order velocity model, to be used for a time-to-depth conversion and for a post-stack GPR data migration, was computed. Moreover, a joint visualization of both datasets (GPR and TLS) was achieved in a novel tridimensional workspace. This solution provided a more straightforward and efficient way of testing the reliability of the combined results, proving the efficiency of the proposed method in the estimation of a velocity model, especially in comparison to conventional GPR methods. This demonstrates how the integration of different remote sensing methodologies can yield a more solid interpretation, taking into account the uncertainties related to the geometrical irregularities of the external wall’s surface and the inner structure generating complex GPR signatures. Full article

Terrestrial laser scanning (TLS) point clouds require high-precision registration and georeferencing to be used effectively. Only then can data from multiple stations be integrated and transformed from the instrument’s local coordinate system into a common, stable reference frame that ensures temporal consistency for further analyses of displacement and deformation. The article demonstrates the validation of an innovative referencing system devised to improve the reliability and accuracy of registering and georeferencing TLS point clouds. The primary component of the system is openable reference spheres, whose centroids can be directly and precisely determined using surveying methods. It also includes dedicated adapters: tripods and adjustable F-clamps with which the spheres can be securely mounted on various structural components, facilitating the optimal distribution of the reference markers. Laboratory tests with four modern laser scanners (Z+F Imager 5010C, Riegl VZ-400, Leica ScanStation P40, and Trimble TX8) revealed sub-millimetre accuracy of sphere fit and form errors, along with the sphere distance error within the acceptance threshold. This confirms that there are no significant systematic errors and that the system is fully compatible with various TLS technologies. The registration and georeferencing quality parameters demonstrate the system’s stability and repeatability. They were additionally verified with independent control points and geodetic levelling of the centres of the spheres. The system overcomes the critical limitations of traditional reference spheres because their centres can be measured directly using surveying methods. This facilitates registration and georeferencing accuracy on par with, or even better than, that of commercial targets. The proposed system serves as a stable and repeatable reference frame suitable for high-precision engineering applications, deformation monitoring, and longitudinal analyses. Full article

Terrestrial Laser Scanners (TLS), as monostatic LiDAR systems, emit and receive laser pulses through a single aperture, which ensures the simultaneous measurement of signal geometry and intensity. The relative intensity of a signal, defined as the ratio of received to transmitted power, directly describes the strength and quality of the reflected signal and the corresponding radiometric uncertainty of individual points. The LiDAR range equation provides the physical connection for characterizing signal strength as a function of reflectivity and other spatial parameters. In this research, theoretical developments of the texture-dependent LiDAR range equation, in conjunction with a neural network method, are presented. The two-step approach aims to improve the accuracy of signal intensities by enhancing signal reflectivity estimation and the precision of signal intensities by reducing their sensitivity to variations in spatial characteristics—range and incidence angle. This establishes the intensity as the standard fourth dimension of the 3D point cloud based on the inherent target quality. For validation, four terrestrial laser scanners—Leica ScanStation P50, Leica ScanStation C10, Leica RTC360, and Trimble X9—are evaluated. Results demonstrate significant improvements of at least 40% in accuracy and 97% in precision for the color intensities of individual points across the devices. This research enables a 4D TLS point cloud calibration framework for further investigations on other internal and external geometries of targets (target materials, roughness, albedo, and edgy and tilted surfaces), which allows the standardization of radiometric values. Full article

Terrestrial laser scanners (TLS) are widely used for deformation monitoring due to their ability to rapidly generate 3D point clouds. However, high-precision deliverables are increasingly required in TLS-based remote sensing applications to distinguish between measurement accuracies and actual geometric displacements. This study addresses the impact of atmospheric refraction, a primary source of systematic error in long-range terrestrial laser scanning, which causes laser beams to deviate from their theoretical path and intersect different object points on the target surface. A comprehensive study of two physical refractive index models (Ciddor and Closed Formula) is presented here, along with further developments on 3D spatial gradients of the refractive index. Field experiments were conducted using two long-range terrestrial laser scanners (Leica ScanStation P50 (Leica Geosystems, Heerbrugg, Switzerland) and Maptek I-Site 8820 (Maptek, Adelaide, Australia)) with reference back to a control network at two monitoring sites: a mine site for long-range measurements and a dam site for vertical angle measurements. The results demonstrate that, while conventional physical atmospheric models provide moderate improvement in accuracy, typically at the centimeter- or millimeter-level, the proposed advanced physical model—incorporating refractive index gradients—and the hybrid physical model—combining validated field results from the advanced model with a neural network algorithm—consistently achieve reliable millimeter-level accuracy in 3D point coordinates, by explicitly accounting for refractive index variations along the laser path. The robustness of these findings was further confirmed across different scanners and scanning environments. Full article

This paper presents the results of laboratory research regarding the influence of the structure and color of decorative renders on the accuracy of measurements conducted using Leica ScanStation P40 terrestrial laser scanning (TLS). The study examined whether and how differences in render structure and color (brightness) affect the quality of data acquired via TLS. The color and brightness measurements of the test fields were performed using a flatbed scanner. The RGB color and luminance analysis of the test fields were conducted using the software “ImageJ” version 1.54g. The measurements were conducted for light-colored renders (average brightness from 143 to 243). The research found no clear relationship established between the type and color of render and the accuracy of laser scanning. The results indicate increased measurement dispersion with decreasing render brightness. It was found that the standard deviation of distance measurements for Scratched-type renders is approximately 26% higher than for Roughcast-type render. Full article

Documenting cultural heritage sites through 3D reconstruction is crucial and can be accomplished using various geomatic techniques, such as Terrestrial Laser Scanners (TLS), Close-Range Photogrammetry (CRP), and UAV photogrammetry. Each method comes with different levels of complexity, accuracy, field times, post-processing requirements, and costs, making them suitable for different types of restitutions. Recently, research has increasingly focused on user-friendly and faster techniques, while also considering the cost–benefit balance between accuracy, times, and costs. In this scenario, photogrammetry using images captured with 360-degree cameras and LiDAR sensors integrated into Apple devices have gained significant popularity. This study proposes the application of various techniques for the geometric reconstruction of a complex cultural heritage site, the Church of Saint Andrew in Orani, Sardinia. Datasets acquired from different geomatic techniques have been evaluated in terms of quality and usability for documenting various aspects of the site. The TLS provided an accurate model of both the interior and exterior of the church, serving as the ground truth for the validation process. UAV photogrammetry offered a broader view of the exterior, while panoramic photogrammetry from 360° camera was applied to survey the bell tower’s interior. Additionally, CRP and Apple LiDAR were compared in the context of a detailed survey. Full article

Detecting trees accurately from terrestrial laser scanning (TLS) point clouds is crucial for processing terrestrial LiDAR data in individual tree analyses. Due to the heterogeneity of savanna ecosystems, our understanding of how various segmentation methods perform on savanna trees remains limited. Therefore, we compared two segmentation algorithms based on the ecological theory of resource distribution, which enables the prediction of the branching geometry of plants. This approach suggests that the shortest path along the vegetation from a point on the tree to the ground remains within the same tree. The algorithms were tested on a 15.2 ha plot scanned at 0.025° resolution during the dry season, using a Riegl VZ1000 Terrestrial Laser Scanner (TLS) in October 2019 at the Skukuza Flux Tower in Kruger National Park, South Africa. Individual tree segmentation was performed on the cloud using the comparative shortest-path (CSP) algorithm, implemented in LiDAR 360 (v 5.4), and the shortest path-based tree isolation method (SPBTIM), implemented in MATLAB (R2022a). The accuracy of each segmentation method was validated using 125 trees that were segmented and manually edited. Results were evaluated using recall (r), precision (p), and the F-score (F). Both algorithms detected (recall) 90% of the trees. The SPBTIM achieved a precision of 91%, slightly higher than the CSP’s 90%. Overall, both methods demonstrated an F-score of 0.90, indicating equal segmentation accuracy. Our findings suggest that both techniques can reliably segment savanna trees, with no significant difference between them in practical application. These results provide valuable insights into the suitability of each method for savanna ecosystems, which is essential for ecological monitoring and efficient TLS data processing workflows. Full article

Given its considerable cultural, historical, and economic value, built heritage requires the application of modern techniques for effective documentation and conservation. While multiple sensors are available for 3D modeling, laser scanning remains the most commonly employed due to its efficiency, precision, and ability to comprehensively capture the building’s geometry, surface textures, and structural details. This results in highly detailed 3D representations that are very important for accurate documentation, analysis, and conservation planning. This study investigates the complementary potential of different 3D modeling approaches for the digital representation of the Dosoftei House in Iasi, a monument of historical significance. For this purpose, an integrated point cloud was created based on a mobile hand-held laser scanner (HMLS), i.e., the FJD Trion P1 and a terrestrial laser scanner (TLS), i.e., the Maptek I-Site 8820 long-range laser scanner, the latter specifically used to capture the roof structures. Based on this dataset, a parametric model was created in Revit, supported by panoramic images, allowing for a structured representation useful in technical documentation and heritage management. In parallel, a mesh model was generated in CloudCompare using Poisson surface reconstruction. The comparison of the two methods highlights the high geometric accuracy of the mesh model and the Building Information Modeling (BIM) model’s capability to efficiently manage information linked to architectural elements. While the mesh provides detailed geometry, the BIM model excels in information organization and supports informed decision-making in conservation efforts. This research proposes leveraging the advantages of both methods within an integrated workflow, applicable on a larger scale in architectural heritage conservation projects. Full article

Accurate extraction of the arch profile, the key spatial geometric parameter of the core load-bearing component in arch bridges, is crucial for construction process control and for achieving the designed final bridge configuration. To overcome the limitations of existing methods—geometric information loss, sensitivity to noise, and inefficiency—when extracting continuous, precise profiles from point clouds of complex spatially curved arch ribs, this paper proposes a multi-step point cloud processing workflow. The approach integrates geometric feature constraints specific to arch bridges to enable automated, high-precision extraction of the arch profile during construction. The approach comprises three steps. First, arch point cloud subset partitioning: the primitive arch point cloud is efficiently divided using parameters from down-sampling arch point cloud data. Second, component segmentation: a Random Sample Consensus (RANSAC) algorithm, optimized with cylindrical geometric constraints, is then employed to precisely segment the point cloud of individual arch tube components from each subset point cloud. Third, arch profile extraction: the geometric invariance of the bottom edge of each arch tube is leveraged to identify feature points via local coordinate system transformation and longitudinal constraints. These feature points are then spliced together to reconstruct the complete arch profile. The proposed method is employed in multiple construction stages of a concrete-filled steel tubular (CFST) arch bridge and quantifies the vertical deformation between adjacent stages. Compared with Total Station (TS) measurements, the average error ranged from 0.24 mm to 4.13 mm, with an overall average error of 2.105 mm, demonstrating accuracy and reliability. Full article

This article presents a novel fully automatic indoor surveying (FAIS) framework for large-scale indoor environments using a Terrestrial Laser Scanning (TLS) hardware system. Traditional methods for indoor surveying are labor-intensive and time-consuming, as they rely on manually positioning scanners for data capture and placing markers for registration. What is more, positioning scanners manually may cause uneven scanning or rescanning, including unstructured areas specifically. To ensure full coverage of the scene, we precisely obtain the number and location of scan stations through the Signed Distance Function (SDF) based method. Meanwhile, we propose an efficient large-scale dense point cloud registration method without markers. The proposed framework is adapted to environments where the scanner operates on a flat surface, such as office spaces, theater stage spaces, urban areas, and some cultural heritage scenic areas. Experiments demonstrate that the proposed method decreases computation time and obtains a more complete point cloud. Full article