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This article describes procedures and thoughts regarding the reconstruction of geometry-given data and its uncertainty. The data are considered as a continuous fuzzy point cloud, instead of a discrete point cloud. Shape fitting is commonly performed by minimizing the discrete Euclidean distance; however, we propose the novel approach of using the expected Mahalanobis distance. The primary benefit is that it takes both the different magnitude and orientation of uncertainty for each data point into account. We illustrate the approach with laser scanning data of a cylinder and compare its performance with that of the conventional least squares method with and without random sample consensus (RANSAC). Our proposed method fits the geometry more accurately, albeit generally with greater uncertainty, and shows promise for geometry reconstruction with laser-scanned data. [ABSTRACT FROM AUTHOR]

Plant phenotyping plays a crucial role in crop science and plant breeding. However, traditional methods often involve time-consuming and manual observations. Therefore, it is essential to develop automated, sensor-driven techniques that can provide objective and rapid information. Various methods rely on camera systems, including RGB, multi-spectral, and hyper-spectral cameras, which offer valuable insights into plant physiology. In recent years, 3D sensing systems such as laser scanners have gained popularity due to their ability to capture structural plant parameters that are difficult to obtain using spectral sensors. Unlike images, point clouds are not structured and require pre-processing steps to extract precise information and handle noise or missing points. One approach is to generate mesh-based surface representations using triangulation. A key challenge in the 3D surface reconstruction of plants is the pre-processing of point clouds, which involves removing non-plant noise from the scene, segmenting point clouds from populations to individual plants, and further dividing individual plants into their respective organs. In this study, we will not focus on the segmentation aspect but rather on the other pre-processing steps, like denoising parameters, which depend on the data type. We present an automated pipeline for converting high-resolution point clouds into surface models of plants. The pipeline incorporates additional pre-processing steps such as outlier removal, denoising, and subsampling to ensure the accuracy and quality of the reconstructed surfaces. Data were collected using three different sensors: a handheld scanner, a terrestrial laser scanner (TLS), and a mobile mapping platform, under varying conditions from controlled laboratory environments to complex field settings. The investigation includes five different plant species, each with distinct characteristics, to demonstrate the potential of the pipeline. In a next step, phenotypic traits such as leaf area, leaf area index (LAI), and leaf angle distribution (LAD) were calculated to further illustrate the pipeline's potential and effectiveness. The pipeline is based on the Open3D framework and is available open source. [ABSTRACT FROM AUTHOR]

Building information modeling (BIM) is the hottest topic of the last decade in the construction sector. BIM is interacting with other technologies toward the realization of digital twins. The integration of laser scanning technology and BIM is progressing. Increasingly, solid, mesh models are being semantically enriched for BIM. A point cloud can provide an excellent source of data for developing a BIM model. The BIM model will be refined not only geometrically but can also be saturated with non-graphical data. The problem is the lack of a clear methodology for compiling such models based on TLS and images. The research and development work between universities and companies has put modern digital solutions into practice. Thus, the purpose of this work was to develop a universal methodology for the acquisition and extraction of data from disconnected sources. In this paper, three BIM models were made based on point clouds derived from laser scanning. The case studies presented confirm the validity of the "scan to BIM approach, especially in the context of historic buildings (HBIMs). The paper posits that the integration of laser scanning, digital photogrammetry and BIM provides value in the preservation of heritage buildings. In the process of the practical work and an in-depth literature study, the ever-present limitations of BIM were identified as research challenges. The paper contributes to the discussion on the use of BIM in the design, construction and operation of buildings, including historic buildings. The acronym HBIM (heritage building information modeling) will increasingly resonate in the academic and practical work of the discipline of conservation and maintenance of historic buildings and cultural heritage sites. [ABSTRACT FROM AUTHOR]

In recent years, 3D digitalisation has experienced significant growth, revolutionising the way we capture, process and use geometric data. Initially conceived for industrial applications, these technologies have expanded to multiple fields, offering unprecedented accuracy and versatility. Depending on the accuracy and efficiency to be achieved in a specific field of application, and on the analytical capacity, a specific 3D digitalisation technique or another will be used. This review aims to delve into the application of 3D scanning techniques, according to the implementation sector. The optimal geometry capturing and processing 3D data techniques for a specific case are studied as well as their limitations. [ABSTRACT FROM AUTHOR]

Point cloud data acquired by scanning with Light Detection and Ranging (LiDAR) devices typically contain irregular objects, such as trees, which lead to low classification accuracy in existing point cloud classification methods. Consequently, this paper proposes a deep point feature aggregation network (DPFANet) that integrates adaptive graph convolution and space-filling curve sampling modules to effectively address the feature extraction problem for irregular object point clouds. To refine the feature representation, we utilize the affinity matrix to quantify inter-channel relationships and adjust the input feature matrix accordingly, thereby improving the classification accuracy of the object point cloud. To validate the effectiveness of the proposed approach, a TreeNet dataset was created, comprising four categories of tree point clouds derived from publicly available UAV point cloud data. The experimental findings illustrate that the model attains a mean accuracy of 91.4% on the ModelNet40 dataset, comparable to prevailing state-of-the-art techniques. When applied to the more challenging TreeNet dataset, the model achieves a mean accuracy of 88.0%, surpassing existing state-of-the-art methods in all classification metrics. These results underscore the high potential of the model for point cloud classification of irregular objects. [ABSTRACT FROM AUTHOR]

Pavement skid resistance is significant for driving safety. British Pendulum Number (BPN) is commonly used as a low-speed skid resistance indicator, whereas sometimes it is impractical for data collection on roads in service. Since skid resistance is greatly affected by pavement surface texture, this research aims to evaluate pavement surface texture comprehensively and estimate the low-speed friction BPN from road surface texture on macro- and micro- scale. Asphalt Concrete (AC) and Stone Mastic Asphalt (SMA) were included. Road surface texture was evaluated from four aspects, texture depth, amplitude-related Root Means Square (RMS), elevation variances corresponding to different wavebands and texture spectral analysis. Texture depth indicators include Mean Texture Depth (MTD) and Mean Profile Depth (MPD). Elevation variances with three wavebands, from 5 mm to 50 mm, from 0.5 mm to 5 mm and from 0.024 mm to 0.5 mm respectively, were obtained. The results show that MPD is well correlated with MTD. Elevation variances with different wavebands demonstrates that the elevation variance of macro-texture with long wavelengths from 5 mm to 50 mm dominates the total variance. Spectral analysis shows that texture level is larger when the wavelength is beyond 4 mm, which is consistent with elevation variances. A linear regression between BPN and single texture index, as well as multiple linear regression analysis were conducted. The former regression result indicates that it is not feasible to estimate BPN using single index due to low correlation coefficient R2. The latter shows that the BPN can be estimated from texture levels corresponding to 64 mm and 2 mm, and the micro-texture. The R2 can be up to 0.684. This research will contribute to fast acquisition of BPN from pavement surface texture, thus improving skid resistance. [ABSTRACT FROM AUTHOR]

The rapid technological development that geomatics has been experiencing in recent years is leading to increasing ease, productivity and reliability of three-dimensional surveys, with portable laser scanner systems based on Simultaneous Localization and Mapping (SLAM) technology, gradually replacing traditional techniques in certain applications. Although the performance of such systems in terms of point cloud accuracy and noise level has been deeply investigated in the literature, there are fewer works about the evaluation of their use for surface reconstruction, cartographic production, and as-built Building Information Model (BIM) creation. The objective of this study is to assess the suitability of SLAM devices for surface modeling in an urban/architectural environment. To this end, analyses are carried out on the datasets acquired by three commercial portable laser scanners in the context of a benchmark organized in 2023 by the Italian Society of Photogrammetry and Topography (SIFET). In addition to the conventional point cloud assessment, we propose a comparison between the reconstructed mesh and a ground-truth model, employing a model-to-model methodology. The outcomes are promising, with the average distance between models ranging from 0.2 to 1.4 cm. However, the surfaces modeled from the terrestrial laser scanning point cloud show a level of detail that is still unmatched by SLAM systems. [ABSTRACT FROM AUTHOR]

This study investigates the utilization of 3D laser scanning, GPS, BIM and GIS technologies for safeguarding historical wooden structures. As a case study, it focuses on two historic Chinese wooden buildings, the Guanyin Pavilion and Tangwang Palace, renowned for their exceptional historical significance and intricate timber architecture. The Guanyin Pavilion was subjected to high-precision modeling and tilt monitoring, which found that certain columns had a maximum tilt angle of 0.7892°. Additionally, a general tilt tendency was seen across various structural elements. The measurements from the point cloud data exhibited an error range of ±10 mm. However, the relative errors in smaller components approached 2.5%, which necessitated regular verification through human measurements. Using GIS and BIM technology in Tangwang Palace facilitated the meticulous documentation and dynamic supervision of architectural components, encompassing historical development and present state. The maintenance records revealed persistent problems with the roof tiles and wooden beams, exposing structural vulnerabilities. During various maintenance intervals, it was observed that the roof tiles were frequently loose and separated, indicating potential flaws in the design or materials used. The application of these modern technologies enhances the effectiveness and precision of conservation efforts and provides a robust scientific foundation for the continuous monitoring and study of cultural heritage. [ABSTRACT FROM AUTHOR]

Global pose refinement is a significant challenge within Simultaneous Localization and Mapping (SLAM) frameworks. For LIDAR-based SLAM systems, pose refinement is integral to correcting drift caused by the successive registration of 3D point clouds collected by the sensor. A divergence between the actual and calculated platform paths characterizes this error. In response to this challenge, we propose a linear, parameter-free model that uses a closed circuit for global trajectory corrections. Our model maps rotations to quaternions and uses Spherical Linear Interpolation (SLERP) for transitions between them. The intervals are established by the constraint set by the Least Squares (LS) method on rotation closure and are proportional to the circuit's size. Translations are globally adjusted in a distinct linear phase. Additionally, we suggest a coarse-to-fine pairwise registration method, integrating Fast Global Registration and Generalized ICP with multiscale sampling and filtering. The proposed approach is tested on three varied datasets of point clouds, including Mobile Laser Scanners and Terrestrial Laser Scanners. These diverse datasets affirm the model's effectiveness in 3D pose estimation, with substantial pose differences and efficient pose optimization in larger circuits. [ABSTRACT FROM AUTHOR]

Nature provides us with a wealth of inspiration for the design of bionic functional surfaces. Numerous types of plant leaves with exceptional wettability, anisotropy, and adhesion are extensively employed in many engineering applications. Inspired by the wettability, anisotropy, and adhesion of indocalamus leaves, bionic upper and lower surfaces (BUSs and BLSs) of the indocalamus leaf were successfully prepared using a facile approach combining laser scanning and chemical modification. The results demonstrated the BUSs and BLSs obtained similar structural features to the upper and lower surfaces of the indocalamus leaf and exhibited enhanced and more-controllable wettability, anisotropy, and adhesion. More importantly, we conducted a detailed comparative analysis of the wettability, anisotropy, and adhesion between BUSs and BLSs. Finally, BUSs and BLSs were also explored for the corresponding potential applications, including self-cleaning, liquid manipulation, and fog collection, thereby broadening their practical utility. We believe that this study can contribute to the enrichment of the research on novel biological models and provide significant insights into the development of multifunctional bionic surfaces. [ABSTRACT FROM AUTHOR]

With the development of robotics and vision measurement technology, the use of robots with line laser scanners for 3D scanning and measurement of parts has become a mainstream trend in the field of industrial inspection. Traditional scanning and measuring robots mainly use the teach-in scanning method, which has unstable scanning quality and low scanning efficiency. In this paper, the adaptive sampling method for a free-form surface, which can realize the adaptive distribution of surface measurement points according to the curvature features of free-form surfaces, is proposed first. Then, integrated with the proposed adaptive sampling method, the automatic path planning method is proposed. This method consists of adaptive sampling, scanning attitude calculation based on a quaternion, scanning viewpoint planning based on viewable cones, and scan path generation based on bi-directional scanning. Based on the proposed automatic path planning method, the scanning and measuring robot can obtain complete 3D information of the surface to be measured with high measurement accuracy and efficiency. The performance index of the laser scanner can be fully reached. [ABSTRACT FROM AUTHOR]

Surface micro-texture has been shown to enhance wettability and reduce wear on cutting tools. However, there is limited research on how laser parameters impact the dimensional accuracy of surface texture and its wettability. This study focuses on producing arrayed groove textures on WC/Co cemented carbide surfaces using Nd: YAG laser, evaluating the effect of the laser parameters on surface topography and texture accuracy through microscopic observation and simulation. The results indicate that, with laser parameters such as a number of passes less than 5, approximately 16 W power, scanning speed of 100–150 mm/s, and pulse frequency of 30 kHz, the error between the groove width and laser spot diameter was 4.7%. Additionally, the study explores the impact of the groove texture on surface wettability using the solid droplet method and XPS analysis. Comparative experiments reveal that increased surface roughness enhanced oleophobicity, with surfaces exhibiting high texture accuracy and integrity showing improved oleophobic and spreading properties. Thus, the precise regulation of laser processes is crucial for maintaining surface texture integrity and enhancing surface wettability. [ABSTRACT FROM AUTHOR]

In bridge structure monitoring and evaluation, deformation data serve as a crucial basis for assessing structural conditions. Different from discrete monitoring points, spatially continuous deformation modes provide a comprehensive understanding of deformation and potential information. Terrestrial laser scanning (TLS) is a three-dimensional deformation monitoring technique that has gained wide attention in recent years, demonstrating its potential in capturing structural deformation models. In this study, a TLS-based bridge deformation mode monitoring method is proposed, and a deformation mode calculation method combining sliding windows and surface fitting is developed, which is called the SWSF method for short. On the basis of the general characteristics of bridge structures, a deformation error model is established for the SWSF method, with a detailed quantitative analysis of each error component. The analysis results show that the deformation monitoring error of the SWSF method consists of four parts, which are related to the selection of the fitting function, the density of point clouds, the noise of point clouds, and the registration accuracy of point clouds. The error caused by point cloud noise is the main error component. Under the condition that the noise level of point clouds is determined, the calculation error of the SWSF method can be significantly reduced by increasing the number of points of point clouds in the sliding window. Then, deformation testing experiments were conducted under different measurement distances, proving that the proposed SWSF method can achieve a deformation monitoring accuracy of up to 0.1 mm. Finally, the proposed deformation mode monitoring method based on TLS and SWSF was tested on a railway bridge with a span of 65 m. The test results showed that in comparison with the commonly used total station method, the proposed method does not require any preset reflective markers, thereby improving the deformation monitoring accuracy from millimeter level to submillimeter level and transforming the discrete measurement point data form into spatially continuous deformation modes. Overall, this study introduces a new method for accurate deformation monitoring of bridges, demonstrating the significant potential for its application in health monitoring and damage diagnosis of bridge structures. [ABSTRACT FROM AUTHOR]

The proliferation of digital technologies is substantially transforming inspection methodologies for construction activities. Although the implementation of a three-dimensional (3D) model has emerged as an advantageous, feasible inspection application, the selection of the most suitable 3D models is challenging due to multiple technology options. The primary objectives of this study were to investigate current trends and identify future technologies for 3D models in the construction industry. This study utilized systematic reviews by identifying and selecting quality journals, analyzing selected articles, and conducting content analysis and meta-analysis to identify dominant themes in 3D models. Results showed that the top technologies used to model construction projects are building information models, remote sensing, stereo vision system/photo processing programs, and augmented reality/virtual reality. The main benefits and challenges of these technologies for modeling were also determined. This study identified three areas with significant knowledge gaps for future research: (1) the amalgamation of two or more technologies to overcome project obstacles; (2) solution optimization for inspections in remote areas; and (3) the development of algorithm-based technologies. This research contributes to the body of knowledge by exploring current trends and future directions of 3D model technologies in the construction industry. [ABSTRACT FROM AUTHOR]

The integration of laser scanning technology and Building Information Modelling (BIM) processes offers a transformative approach to managing the complexities in live construction projects. This paper aims to explore the significant impacts of incorporating laser scanning and BIM on construction projects in terms of as-built models, information management, and overall project performance utilising case study analysis of a building that was not BIM-based. The research scope is defined by the need to investigate the integration of laser scanning and BIM in live construction projects. It details the data acquisition process, challenges encountered due to site obstructions, and the methodologies employed for spatial modelling procedures. Key findings reveal that such integration can significantly enhance the accuracy of data collection and improve project outcomes. Results also identify the need for specialised equipment and skills for the effective implementation of such integrations. The research concludes by offering a practical approach to enhancing construction processes, from design to maintenance. This paper contributes to the body of knowledge by providing a detailed analysis of the practical application of laser scanning and BIM in a live construction project, offering insights into the benefits, challenges, and future directions for integrating these technologies in the construction industry. [ABSTRACT FROM AUTHOR]

This paper investigates the utilisation of heritage building information modelling (BIM) in order to improve the architectural heritage documentation process at Ad Deir, a significant historical building within the UNESCO World Heritage site of Petra, Jordan. Ad Deir, also known as 'The Monastery', requires accurate and complete documentation for its preservation and effective management. Traditional documentation methods, such as manual surveys and 2D drawings, frequently fail to obtain the intricate details and complexity of heritage structures. This study proposes the use of heritage BIM, which involves creating a digital representation of Ad Deir by combining various data types such as geometric, material, and historical information. Laser scanning technology is used to capture the site in three dimensions, providing a precise representation of its current state. The point clouds are exported to the BIM workflow once they have been processed. The longitudinal and cross-sections of the point clouds revealed the dimensions of regular and irregular elements, which were then traced and modelled accurately. This digital model serves as a platform for future data integration, which may include historical documentation, architectural plans, and construction details. Creating accurate heritage BIM, which involves various levels of knowledge, improves quality control during conservation work and aids in informed decision-making. [ABSTRACT FROM AUTHOR]

Titanium alloys are considered lightweight alloys and are widely applied across various industries. However, titanium alloys are prone to wearing out or galvanic corrosion. In this paper, Ti6Al4V alloy was scanned by using a continuous laser in different atmospheres to prepare composite hardening coatings. The scanning speed was varied to adjust the heat input. When the alloy was irradiated in air, a whole coating composed of TiO2 and TiN was fabricated. With the increase in scanning speed from 10 mm/s to 20 mm/s, the melting area of the surface decreased from about 1.8 mm to 0 mm, but the thickness of the coatings underwent no significant change. When prepared under compressed oxygen with a speed of 10 mm/s, a coating with a thickness of about 60 μm was prepared. In addition, the layered phenomenon occurred, and an N-enriched layer was formed at the bottom of the coating. The coatings were composed of TiO2, TiN and Ti. With the increase in the scanning speed, the thickness of the coatings decreased obviously. The testing results show that the hardness of samples Ti-A10 and Ti-O10 increased by around 160% and 140% over that of untreated samples, respectively. The anti-corrosion performance of the samples treated via laser scanning was also improved. [ABSTRACT FROM AUTHOR]

The selection of the optimal methodology for the 3D geometric documentation of cultural heritage is a subject of high concern in contemporary scientific research. As a matter of fact, it requires a multi-source data acquisition process and the fusion of datasets from different sensors. This paper aims to demonstrate the workflow for the proper implementation and integration of geodetic, photogrammetric and laser scanning techniques so that high-quality photorealistic 3D models and other documentation products can be generated for a complicated, large-dimensional architectural monument and its surroundings. As a case study, we present the monitoring of the Mehmet Bey Mosque, which is a landmark in the city of Serres and a significant remaining sample of the Ottoman architecture in Greece. The surveying campaign was conducted in the context of the 2022–2023 annual workshop of the Interdepartmental Program of Postgraduate Studies "Protection Conservation and Restoration of Cultural Monuments" of the Aristotle University of Thessaloniki, and it served as a geometric background for interdisciplinary cooperation and decision-making on the monument restoration process. The results of our study encourage the fusion of terrestrial laser scanning and photogrammetric datasets for the 3D modeling of the mosque, as they supplement each other as regards geometry and texture. [ABSTRACT FROM AUTHOR]

The variety of equipment implementing laser triangulation technology for 3D scanning makes it difficult to analyse their performance, comparability, and traceability. In this study, three laser triangulation sensors arranged in different configurations are analysed using high precision spheres made of different materials and surface finishes. Three types of reference parameters were used: diameter, form error, and standard deviation of the point cloud. The experimentation was based on studying the quality of the point clouds generated by the three sensors, which enabled us to find and quantify an edge effect in the horizon of the scanned surface. A procedure to reach the optimal filtering conditions was proposed, and a chart of recommended usage of each sphere (material and finish) was created for the different types of sensors. This filter enables removal of both spurious points and those few points that spoil the form error, greatly improving the quality of the measurement. [ABSTRACT FROM AUTHOR]

This paper discusses an experience developed as part of the 2021 Topographic Survey Workshop, organized by the Department of Cultural Heritage of Ravenna (University of Bologna) in the Roman city of Suasa (Castelleone di Suasa, AN), during which the potential of integrating photogrammetric and laser scanner surveys was explored in order to geometrically and morphologically characterize the remains of the Roman amphitheater. [ABSTRACT FROM AUTHOR]

The paper introduces an innovative methodology that combines photogrammetry and laser scanning techniques to create detailed 3D models of historic mansions within the Kifissia region of Attica, Greece. While photogrammetry excels in capturing intricate textures, it faces challenges such as lighting variations and precise image alignment. On the other hand, laser scanning offers precision in capturing geometric details but struggles with reflective surfaces and large datasets. Our study integrates these methods to leverage their strengths and address limitations, resulting in comprehensive and accurate digital twins of cultural spaces. The methodology section outlines the step-by-step process of integration, emphasizing solutions to specific challenges encountered in the study area. Preliminary results showcase the enhanced fidelity and completeness of the digital twins, demonstrating the effectiveness of the combined approach. The subsequent sections of the paper delve into a detailed presentation of the methodology, provide a comprehensive analysis of obtained results, and discuss the implications of this innovative approach in cultural preservation and broader applications. [ABSTRACT FROM AUTHOR]

This article relies on a combination of digital and analog data to analyze the 2D urban development of al-ʿAqaba and Jallūm districts in the Old City of Aleppo. The dataset consists of vectorized historical maps of the city spanning various historical periods. The oldest map in the collection dates back to the 1900s. Additionally, there are high-resolution orthomosaics created from a 3D model obtained through Terrestrial Laser Scanning (TLS) and Aerial Photogrammetry techniques. Through the analysis and integration of these various data types, the article proposes an analog-digital workflow that tracks the alterations in the urban fabric of the designated study area. The analysis primarily examines the alterations in the city's two-dimensional layout and the distribution of mass and void. Tracking the changes in the street network of the studied area is the main goal of this research, along with recognizing the spatial changes in the built environment. The article identified changes in both the open spaces and the street layout. [ABSTRACT FROM AUTHOR]

The restoration of historic buildings and structures involves a wide range of scientific and technical fields. The grouting process is among an array of rehabilitation and preservation interventions and aims to homogenize the structure after the implementation of strengthening measures. The process can provide important information regarding the state of preservation of the examined structure and correlate the progress of the process with the pathology of the monument. To achieve this, the analysis of typical raw grouting data is progressively fused with additional information from the diagnostic studies, non-destructive testing, geospatial information, and from the calculation and analysis of grouting indices. The restoration project of the Katholikon of the Monastery of Panagia Varnakova in Fokida, Greece was selected as the case study, due to its large scale and the severe earthquake damage it has sustained, which has necessitated comprehensive strengthening interventions and extensive grouting. The implementation of an integrated methodological approach validated the enhanced level of co-analysis, revealing information that is not readily deduced from a typical approach. Selected sub-areas of the Katholikon are presented, demonstrating how the observed pathology can be correlated with the results of the grouting process, while incorporating 3D data, and findings from structural and non-destructive analyses. [ABSTRACT FROM AUTHOR]

This study aims to describe the numerical modeling and nonlinear finite element analysis of typical spinal braces as a first step towards optimizing their topology for 3D printing. Numerical simulation was carried out in Abaqus CAE software Version 2021, utilizing a CAD (Meshmixer Version 3.5.474) scan of an actual spinal brace. Boundary conditions were defined by means of contact surfaces between the human body and the supporting pads located in the interior of the brace. The process of tightening the straps on the rear face of the brace was simulated via appropriate imposed displacements. The response is described through the deformations and developing stresses of the brace and the contact pressures in the areas of interaction with the human body. Parametric analysis indicated that increasing the cross-sectional thickness or elastic modulus of the brace material results in higher maximum von Mises stresses and lower displacements. The comparison between 3D-printed and conventional braces highlighted the potential of 3D-printing technology to achieve comparable performance with customized designs, leveraging the constitutive properties of 3D-printed material obtained from tension tests. The tension tests demonstrated that the 3D-printed material achieved higher values of modulus of elasticity compared to traditional brace materials. Finally, the topology optimization criteria to be applied for the design of spinal braces in the next step of this ongoing research are briefly described. [ABSTRACT FROM AUTHOR]

Understanding the contributions of stream bank and bed erosion will allow us to implement the most effective management practices. The objective of this study was to assess different methods to measure bank and bed erosion at different scales, specifically the watershed, reach and plot. Innovative and traditional methods were utilized. At the watershed scale, indices based on free satellite images were used. For the reach scale, indices were used, but the images with higher accuracy were purchased and captured by unmanned aerial vehicles (UAVs). At the plot scale, erosion pins, cross-sections and laser scanning were applied. The watershed scale analysis showcased "hot spots". These "hot spots" were reaches vulnerable to erosion and deposition. The indices of the purchased images were applied to these "hot spots" and allowed us to narrow the length of the reaches where UAV flights took place. These flight images located where erosion and deposition occurred. Finally, at the plot scale, laser scanning provided more detailed and accurate data at a greater scale compared to the traditional methods. The implementation of these methods allows us to find the areas vulnerable to erosion and deposition. These are the areas where nature-based solutions should be implemented to effectively mitigate erosion problems. [ABSTRACT FROM AUTHOR]

Uneven road surfaces are the primary source of excitation in the dynamic interaction between a bridge and a vehicle and can lead to errors in bridge weigh-in-motion (B-WIM) systems. In order to correctly reproduce this interaction in a numerical model of a bridge, it is essential to know the magnitude and location of the various roadway irregularities. This paper presents a methodology for measuring the 3D road surface using static terrestrial laser scanning and a numerical model for simulating vehicle passage over a bridge with a measured road surface. This model allows the evaluation of strain responses in the time domain at any bridge location considering different parameters such as vehicle type, lateral position and speed, road surface unevenness, bridge type, etc. Since the time domain strains are crucial for B-WIM algorithms, the proposed approach facilitates the analysis of the different factors affecting the B-WIM results. The first validation of the proposed methodology was carried out on a real bridge, where extensive measurements were performed using different sensors, including measurements of the road surface, the response of the bridge when crossed by a test vehicle and the dynamic properties of the bridge and vehicle. The comparison between the simulated and measured bridge response marks a promising step towards investigating the influence of unevenness on the results of B-WIM. [ABSTRACT FROM AUTHOR]

Landslides represent a significant natural hazard with wide-reaching impacts. Addressing the challenge of accurately detecting and monitoring landslides, this research introduces a novel approach that combines feature tracking with histogram analysis for efficient outlier removal. Distinct from existing methods, our approach leverages advanced histogram techniques to significantly enhance the accuracy of landslide detection, setting a new standard in the field. Furthermore, when tested on three different data sets, this method demonstrated a notable reduction in outliers by approximately 15 to 25 percent of all displacement vectors, exemplifying its effectiveness. Key to our methodology is a refined feature tracking process utilizing terrestrial laser scanners, renowned for their precision and detail in capturing surface information. This enhanced feature tracking method allows for more accurate and reliable landslide monitoring, representing a significant advancement in geospatial analysis techniques. [ABSTRACT FROM AUTHOR]

The significance of data acquisition in archaeological practice has consistently held great importance. Over the past few decades, the growing prevalence of digitization in acquiring data has significantly transformed the landscape of archaeological fieldwork, influencing both methodology and interpretation. The integration of digital photogrammetry and laser scanning technologies in archaeology has transformed data acquisition, enabling efficient and precise documentation. However, this digital shift raises concerns about information overload, the potential loss of on-site insights, and the need for suitable data management methods. Over the past 15 years, digital tools like photogrammetry, laser scanning, and unmanned aerial vehicles have advanced cultural heritage documentation. These methods offer detailed 3D models of archaeological sites, artifacts, and monuments, with evolving accessibility and user friendliness. This paper delves into methods for documenting cultural heritage, examining the implications of various approaches on the archaeologist's workflow and on the field as a whole. [ABSTRACT FROM AUTHOR]

Simple Summary: Cranial cruciate ligament (CCL) insufficiency is a common condition in dogs, commonly treated using tibial plateau leveling osteotomy (TPLO). CCL injury often results in secondary abnormalities of the menisci. Arthrotomy is still used by many veterinarians to detect meniscal damage, and also, before TPLO an assessment of the menisci is generally recommended. However, only a limited part of the menisci is visible during arthrotomy of the stifle. Our hypothesis was that the change in tibial plateau position created by TPLO allows a better visual access to the menisci. To verify suspicion, we compared the degree of visibility of the lateral and medial menisci before and after TPLO on 15 identical 3-dimensional (3D)-printed models of a normal canine tibia. On each model, the meniscal area was stained and photographed, and its part visible to the surgeon before and after TPLO was digitally measured and compared. Our modeling showed that before TPLO, without additional instrumentation, e.g., arthroscopy, only approximately 16% of the entire meniscus area was visible. We demonstrated that TPLO increased the visibility of the lateral meniscus to 38–56% (mean ± SD: 46.5 ± 5.4%) of its entire area and of the medial meniscus to 41–70% (mean ± SD: 52.8 ± 7.6%). This increase in the visibility was statistically significant (p < 0.001). We conclude that performing the examination of the menisci after TPLO allows for a review of about 50% of the entire meniscal area, in contrast to examination before TPLO, where only about 16% is visible. The visible area is slightly smaller in the lateral than in the medial meniscus; however, this difference is unlikely to be clinically relevant. The aim of this study was to compare the degree of visibility of the lateral and medial menisci before and after tibial plateau leveling osteotomy (TPLO) on 3D-printed models created after laser scanning of the right tibia with menisci derived from a fresh cadaver of a 4-year-old adult male golden retriever. The models were produced of white polylactic acid, and the menisci were filled with light-curing red resin. The models showed a similar conformation as the natural specimen harvested from the cadaver, maintaining the same length and width, in addition to reproducing the anatomical structures. From the pre- and post-TPLO radiographs, it was possible to identify the anatomical structures corresponding to the tibial plateau. The preoperative tibial plateau angle was 26.2°, and the postoperative one ranged between 4.0° and 5.3° (4.6 ± 0.4°). In the bird's-eye photo, the total number of red pixels in the lateral and the medial meniscus was 2,053,995 and 2,140,939, respectively. Before TPLO, only between 14% and 19% of the entire area of the menisci was visible, and the unhidden part of the entire area of the meniscus before TPLO did not differ significantly between the lateral (16.2 ± 1.6%) and the medial (16.4 ± 1.6%) meniscus (p = 0.351). The visible part of the entire meniscus area increased significantly after TPLO both in the lateral and medial menisci (p < 0.001)—mean difference ± SD of 30.3 ± 4.3% (CI 95%: 27.9%, 32.6%) and 36.4 ± 6.4% (CI 95%: 32.9%, 40.0%), respectively. In conclusion, the intraoperative examination and treatment of dog menisci are easier after TPLO. [ABSTRACT FROM AUTHOR]

Robust and effective fruit detection and localization is essential for robotic harvesting systems. While extensive research efforts have been devoted to improving fruit detection, less emphasis has been placed on the fruit localization aspect, which is a crucial yet challenging task due to limited depth accuracy from existing sensor measurements in the natural orchard environment with variable lighting conditions and foliage/branch occlusions. In this paper, we present the system design and calibration of an Active LAser-Camera Scanner (ALACS), a novel perception module for robust and high-precision fruit localization. The hardware of the ALACS mainly consists of a red line laser, an RGB camera, and a linear motion slide, which are seamlessly integrated into an active scanning scheme where a dynamic-targeting laser-triangulation principle is employed. A high-fidelity extrinsic model is developed to pair the laser illumination and the RGB camera, enabling precise depth computation when the target is captured by both sensors. A random sample consensus-based robust calibration scheme is then designed to calibrate the model parameters based on collected data. Comprehensive evaluations are conducted to validate the system model and calibration scheme. The results show that the proposed calibration method can detect and remove data outliers to achieve robust parameter computation, and the calibrated ALACS system is able to achieve high-precision localization with the maximum depth measurement error being less than 4 mm at distance ranging from 0.6 to 1.2 m. [ABSTRACT FROM AUTHOR]

The emergence of new technologies has dynamized the way in which cultural heritage is documented, preserved, and passed on to new generations; something that determines a paradigm shift in terms of research in this field. Most operations now also have access to the virtual component. In this context, the current study aimed to make accessible through virtual and augmented reality one of the most interesting objectives belonging to the Jewish cultural heritage built in Art Nouveau style in the municipality of Oradea (Romania), which currently functions as a La Belle Epoque Museum. In the study, the techniques of terrestrial, aerial photogrammetry, and terrestrial laser scanning were used to remodel, in a three-dimensional format, as faithful as possible and usable in different applications, the special architecture of the exterior of the monument. This information was doubled by making the interior of the monument accessible through a complete and complex series of panoramic images interconnected within a virtual tour that will be made available to tourists interested in discovering the Darvas-La Roche House. The virtual tour, which includes both graphic, textual, and audio information, represents an innovative approach for the buildings built in Art Nouveau style in the municipality of Oradea, representing a virtual bridge for better promotion of the tourist destination and for the awareness of the local people regarding the importance of preserving and appreciating the local cultural heritage. This is all the more important as this is the first initiative to make the Art Nouveau buildings in Oradea Municipality accessible to the general public in an innovative way. [ABSTRACT FROM AUTHOR]

Recently, point cloud technology has been applied in the ship engineering field. However, the dense point cloud acquired by terrestrial laser scanning (TLS) technology in ship engineering applications brings an obstacle to some powerful and advanced point-based deep learning point cloud processing methods. This paper presents a deep learning pre-procession module to ensure the feasibility of processing dense point clouds on commonly available computer devices. The pre-procession module is designed according to the traditional point cloud processing methods and the PointNet++ paradigm, and is evaluated on two ship structure datasets and two popular point cloud datasets. Experimental results illustrate that (i) the proposed module improves the performance of point-based deep learning semantic segmentation networks, and (ii) the proposed module empowers the existing point-based deep learning networks with the capability to process dense input point clouds. The proposed module may provide a useful semantic segmentation tool for realistic dense point clouds in various industrial applications. [ABSTRACT FROM AUTHOR]

The article delves into the application of laser scanning within the realm of engineering, concentrating its examination on rotary kilns. Through an in-depth case study, this article meticulously assesses the advantages inherent in utilising laser scanning technology and draws comparisons with conventional measurement methods. The overarching objective of the investigation is to unravel the intricate relationship between the deterioration of the rotary kiln liners and the ovality of the underlying steel structure. By meticulously analysing these aspects, this article seeks to contribute valuable insights into the understanding of this complex interplay in the context of engineering practices. As a measurement apparatus, a terrestrial laser scanner was used. The interior and exterior of the rotary kiln were measured. The primary focus object was inner-lining loss and the geometric characteristics of the cylindrical shells. The research uncovered significant disparities in inner lining loss between the sections. A correlation was found between the ovality and elimination of the inner lining. Due to the hypothesis of constant inner lining loss in the middle of the rotary kiln, the investigation found that the loss of brick lining was less than the value reported from the wells. This study offers significant information on the maintenance and repair strategies for rotary kilns, which have the potential to increase their efficiency and useful life. [ABSTRACT FROM AUTHOR]

An abandoned gypsum mine has been discovered beneath the route of a highway construction in Hunan province, south China. Due to the highway construction and operations safety, there is an urgent need for a comprehensive stability analysis of the abandoned mining area. The 3D laser scanning detection technique has been adopted, and over 400 drillholes were strategically placed near the highway to capture the spatial information of the abandoned gypsum mine. The ore body has an average mining thickness of about 3 m, and the depth of the mining roof ranges from 40 to 60 m, with an average span of 16 m. Based on the research achievements in the engineering geological investigation, rock mass quality assessment, and geometry information, a simplified numerical model has been established for stability analysis. The numerical model employed the IMASS rock mass constitutive model to conduct a stability analysis of the abandoned gypsum mine during the excavation process and in the medium to long term. The IMASS constitutive model can effectively reflect the entire process of rock mass from microscopic damage to macroscopic instability, and the numerical simulation of current and long-term stages provides a much greater understanding of the mining room stability and the effect of various geo-mechanical parameters not considered in traditional empirical methods. The abandoned gypsum mine stability is guaranteed in the mining and current stages. However, the numerical results showed that a 0.4 m spalling thickness of the sidewalls can cause an overall instability and failure of the abandoned mine, and reinforcement measures must be taken for long-term safety. The stability of the abandoned gypsum mine with filling solutions was also evaluated numerically. [ABSTRACT FROM AUTHOR]

This study introduces two innovative methods in the research for use in vision-based tunnel inspection vehicles. First, the image-range stitching method is used to map the sequence images acquired by a camera onto a tunnel layout map. This method reduces the tunnel image-stitching problem to the appropriate parameters, thus solving the problem of mapping equations, ranging from camera pixels to the tunnel layout map. The parameters are obtained using a laser scanner. Secondly, traditional label-based deep learning solely perceives the consistency between pixels and semantically labeled samples, making it challenging to effectively address issues with uncertainty and multiplicity. Consequently, we introduce a method that employs a bidirectional heuristic search approach, utilizing randomly generated seed pixels as hints to locate targets that concurrently appear in both the image and the image semantic generation model. The results reveal the potential for cooperation between laser-scanning and camera-imaging technologies and point out a novel approach of crack detection that appears to be more focused on semantic understanding. [ABSTRACT FROM AUTHOR]

The deterioration of farmland shelterbelts in the Ulan Buh desert oases could weaken their protective functions. Therefore, an accurate method is essential to assess tree decline degree in order to guide the rejuvenation and transformation of these shelterbelts. This study selected three typical farmland shelterbelts in the Ulan Buh desert oases as the objects. Terrestrial laser scanning (TLS) and airborne hyperspectral imagery (AHI) were used to acquire point cloud data and detailed spectral information of trees. Point cloud and spectral characteristics of trees with varying decline levels were analyzed. Six models were constructed to identify decline degree of shelterbelts, and model accuracy was evaluated. The coefficient of determination between the structural parameters of trees extracted by TLS and field measurements ranged from 0.76 to 0.94. Healthy trees outperformed declining trees in structural parameters, particularly in tridimensional green biomass and crown projection area. Spectral reflectance changes in the 740–950 nm band were evident among the three tree types with different decline levels, decreasing significantly with increased decline level. Among the TLS-derived feature parameters, the canopy relief ratio of tree points and point cloud density strongly correlated with the degree of tree decline. The plant senescence reflectance index and normalized difference vegetation index exhibited the closest correlation with tree decline in AHI data. The average accuracy of the models constructed based on the feature parameters of LiDAR, AHI, and the combination of both of them were 0.77, 0.61, and 0.81, respectively. The light gradient-boosting machine model utilizing TLS–AHI comprehensive feature parameters accurately determined tree decline. This study highlights the efficacy of employing feature parameters derived from TLS alone to accurately identify tree decline. Combining feature parameters from the TLS and AHI enhances the precision of tree decline identification. This approach offers guidance for decisions regarding the renewal and transformation of declining farmland shelterbelts. [ABSTRACT FROM AUTHOR]

In recent years, researchers in the field of natural heritage have intensified their efforts to develop new ways to enhance the promotion and accessibility of natural content in order to attract more audiences using virtual representations of physical objects (digital twins). Therefore, they are increasingly incorporating new technologies and digital tools in their operations since their usage by the general public and in the natural heritage (NH) museums is considered particularly effective. Simultaneously, the increasing quality of the produced digitizations has opened up new opportunities for the exploitation of the outcomes of digitization beyond the initial anticipations. Responding to the growing demand of museum visitors for a personalized digital tour experience, especially amidst the recent COVID-19 pandemic, the v-PalM project aims to develop a digital platform to offer virtual guidance and education services at the Museum of Paleontology and Geology, which is hosted at the National Kapodistrian University of Athens. The development of the platform will be based on collecting data through various methods, including crowdsourcing, innovative information, and communication technologies, taking advantage of content digitization using 3D scanning devices. This paper demonstrates an enhanced methodology for the digitization of paleontological exhibits. The methodology uses photogrammetry and laser scanning methods from various devices, such as drones, laser scanners, and smartphones. These methods create digital twins that are suitable for various scenarios, including research, education, and entertainment. The proposed methodology has been applied to over fifty paleontological museum exhibits of varying sizes and complexities, and the resulting 3D models exhibit high accuracy in both their material and geometric aspects, while they also feature crucial details that assist researchers and the scientific community. [ABSTRACT FROM AUTHOR]

This contribution focuses on a comparison of modern geomatics technologies for the derivation of growth parameters in forest management. The present text summarizes the results of our measurements over the last five years. As a case project, a mountain spruce forest with planned forest logging was selected. In this locality, terrestrial laser scanning (TLS) and terrestrial and drone close-range photogrammetry were experimentally used, as was the use of PLS mobile technology (personal laser scanning) and ALS (aerial laser scanning). Results from the data joining, usability, and economics of all technologies for forest management and ecology were discussed. ALS is expensive for small areas and the results were not suitable for a detailed parameter derivation. The RPAS (remotely piloted aircraft systems, known as "drones") method of data acquisition combines the benefits of close-range and aerial photogrammetry. If the approximate height and number of the trees are known, one can approximately calculate the extracted cubage of wood mass before forest logging. The use of conventional terrestrial close-range photogrammetry and TLS proved to be inappropriate and practically unusable in our case, and also in standard forestry practice after consultation with forestry workers. On the other hand, the use of PLS is very simple and allows you to quickly define ordered parameters and further calculate, for example, the cubic volume of wood stockpiles. The results from our research into forestry show that drones can be used to estimate quantities (wood cubature) and inspect the health status of spruce forests, However, PLS seems, nowadays, to be the best solution in forest management for deriving forest parameters. Our results are mainly oriented to practice and in no way diminish the general research in this area. [ABSTRACT FROM AUTHOR]

Point cloud models are prevalently utilized in the architectural and civil engineering sectors. The registration of point clouds can invariably introduce registration errors, adversely impacting the accuracy of point cloud models. While the domain of computer vision has delved profoundly into point cloud registration, limited research in the construction domain has explored these registration algorithms in the built environment, despite their inception in the field of computer vision. The primary objective of this study is to investigate the impact of mainstream point cloud registration algorithms—originally introduced in the computer vision domain—on point cloud models, specifically within the context of bridge engineering as a category of civil engineering data. Concurrently, this study examines the influence of noise removal on varying point cloud registration algorithms. Our research quantifies potential variables for registration quality based on two metrics: registration error (RE) and time consumption (TC). Statistical methods were employed for significance analysis and value engineering assessment. The experimental outcomes indicate that the GRICP algorithm exhibits the highest precision, with RE values of 3.02 mm and 2.79 mm under non-noise removal and noise removal conditions, respectively. The most efficient algorithm is PLICP, yielding TC values of 3.86 min and 2.70 min under the aforementioned conditions. The algorithm with the optimal cost-benefit ratio is CICP, presenting value scores of 3.57 and 4.26 for non-noise removal and noise removal conditions, respectively. Under noise removal conditions, a majority of point cloud algorithms witnessed a notable enhancement in registration accuracy and a decrease in time consumption. Specifically, the POICP algorithm experienced a 32% reduction in RE and a 34% decline in TC after noise removal. Similarly, PLICP observed a 34% and 30% reduction in RE and TC, respectively. KICP showcased a decline of 23% in RE and 28% in TC, CICP manifested a 27% and 31% drop in RE and TC, respectively, GRICP observed an 8% reduction in RE and a 40% decline in TC, and for FGRICP, RE and TC decreased by 8% and 52%, respectively, subsequent to noise removal. [ABSTRACT FROM AUTHOR]

The diffuse data fruition of archaeological hypogeum sites still represents a challenge due to their limited accessibility and their preservation and maintenance issues. This implies that the fruition of these peculiar archaeological sites is often possible through digital reconstructions and interactive web navigation systems. The survey methodologies based on terrestrial laser scanning and photogrammetry allow making accurate and detailed digital reconstructions of these sites that are useful for virtual fruition purposes. In addition, many different systems can be used for remote web navigation and fruition. This work presents a possible solution for the virtual fruition of archaeological hypogea with a multiscale 3D web navigation system based on WebGL open-source technology. The system has been implemented for the Roman hypogeum of Crispia salvia, located in Marsala (southern Italy). The hypogeum belongs to the Archaeological Park of Lilibeo-Marsala and is considered one of the most important archaeological discoveries in this area for its extraordinary frescoes. Public accessibility of this site is limited because it is located outside the boundaries of the Archaeological Park, in the modern town, and covered by a residential building. In this case, the web navigation system adds an important contribution due to the limited real accessibility to the site. This work shows the framework for the construction of the web navigation system, where 3D surveys, digital reconstructions, 3D modeling, and web development are integrated. The choice of using an open-source technology for the web navigation system limits the costs of the process, and, at the same time, grants the web dissemination of site information. [ABSTRACT FROM AUTHOR]

Technological developments involving the implementation of modern measuring equipment and the digitalisation of civil engineering can contribute to extending the service life of buildings. Large-panel buildings constitute a large housing stock throughout Europe. This paper presents the possibility of using laser scanning to identify typical assembly defects in large-panel buildings. Based on point cloud data, numerical models were created to assess the impact of improper assembly on the elements' performance. It was indicated that using scanning to identify and monitor the displacement of structural elements does not relieve experts of the need to perform other tests. Analyses related to the possibility of using Building Information Modeling technology to manage large-panel buildings were also conducted. A parametric model was made, from which a number of possibilities of its use at every stage of the building's life were presented in an example. It was highlighted that parametric models of large-panel buildings, due to their repeatable geometry, can be copied for use in managing entire neighbourhoods. Limitations associated with implementing BIM technology in practice were also formulated. The analyses and research performed confirm the validity of implementing modern research methods in engineering practice and digitising the documentation of large-panel buildings. [ABSTRACT FROM AUTHOR]

The orography of the terrain is a key factor for the electrification of vehicles, especially regarding public transport and electric buses. This work deals with the analysis of the use of mobile laser scanning, both terrestrial and aerial, for the evaluation of the orography of urban areas. First, the minimum point density required is evaluated to estimate the slope. The results show that point densities of 1 point/m2, measured with aerial laser scanning, are adequate for the task. Based on this, the design of a route for public transport is presented including the requirements concerning key transit points, maximum slope, and others. Based on the proposed route design, the transformation to an electrified route is analyzed from an economic and environmental point of view. The results show that the implementation of electric buses vs. diesel buses in cities with steep slopes (up to 7%) reduces greenhouse gas emissions (32.59%) as well as economic costs (18.10%). [ABSTRACT FROM AUTHOR]

Point cloud processing is an essential task in many applications in the AEC domain, such as automated progress assessment, quality control and 3D reconstruction. As much of the procedure used to process the point clouds is shared among these applications, we identify common processing steps and analyse relevant algorithms found in the literature published in the last 5 years. We start by describing current efforts on both progress and quality monitoring and their particular requirements. Then, in the context of those applications, we dive into the specific procedures related to processing point clouds acquired using laser scanners. An emphasis is given to the scan planning process, as it can greatly influence the data collection process and the quality of the data. The data collection phase is discussed, focusing on point cloud data acquired by laser scanning. Its operating mode is explained and the factors that influence its performance are detailed. Data preprocessing methodologies are presented, aiming to introduce techniques used in the literature to, among other aspects, increase the registration performance by identifying and removing redundant data. Geometry extraction techniques are described, concerning both interior and outdoor reconstruction, as well as currently used relationship representation structures. In the end, we identify certain gaps in the literature that may constitute interesting topics for future research. Based on this review, it is evident that a key limitation associated with both Scan-to-BIM and Scan-vs-BIM algorithms is handling missing data due to occlusion, which can be reduced by multi-platform sensor fusion and efficient scan planning. Another limitation is the lack of consideration for laser scanner performance characteristics when planning the scanning operation and the apparent disconnection between the planning and data collection stages. Furthermore, the lack of representative benchmark datasets is hindering proper comparison of Scan-to-BIM and Scan-vs-BIM techniques, as well as the integration of state-of-the-art deep-learning methods that can give a positive contribution in scene interpretation and modelling. [ABSTRACT FROM AUTHOR]

This paper focuses on the 3D modeling of the interior spaces of buildings. Three-dimensional point clouds from laser scanners can be considered the most widely used data for 3D indoor modeling. Therefore, the walls, ceiling and floor are extracted as the main structural fabric and reconstructed. In this paper, a method is presented to tackle the problems related to the data including obstruction, clutter and noise. This method reconstructs indoor space in a model-driven approach using watertight predefined models. Employing the two-step implementation of this process, the algorithm is able to model non-rectangular spaces with an even number of sides. Afterwards, an "improvement" process increases the level of details by modeling the intrusion and protrusion of the model. The 3D model is formed by extrusion from 2D to 3D. The proposed model-driven algorithm is evaluated with four benchmark real-world datasets. The efficacy of the proposed method is proved by the range of [77%, 95%], [85%, 97%] and [1.7 cm, 2.4 cm] values of completeness, correctness and geometric accuracy, respectively. [ABSTRACT FROM AUTHOR]

Synergies of optical, thermal and laser scanning remotely sensed data provide valuable information to study the structure and functioning of terrestrial ecosystems. One of the few fully operational airborne multi-sensor platforms for ecosystem research in Europe is the Flying Laboratory of Imaging Systems (FLIS), operated by the Global Change Research Institute of the Czech Academy of Sciences. The system consists of three commercial imaging spectroradiometers. One spectroradiometer covers the visible and near-infrared, and the other covers the shortwave infrared part of the electromagnetic spectrum. These two provide full spectral data between 380–2450 nm, mainly for the assessment of biochemical properties of vegetation, soil and water. The third spectroradiometer covers the thermal long-wave infrared part of the electromagnetic spectrum and allows for mapping of surface emissivity and temperature properties. The fourth instrument onboard is the full waveform laser scanning system, which provides data on landscape orography and 3D structure. Here, we describe the FLIS design, data acquisition plan and primary data pre-processing. The synchronous acquisition of multiple data sources provides a complex analytical and data framework for the assessment of vegetation ecosystems (such as plant species composition, plant functional traits, biomass and carbon stocks), as well as for studying the role of greenery or blue-green infrastructure on the thermal behaviour of urban systems. In addition, the FLIS airborne infrastructure supports calibration and validation activities for existing and upcoming satellite missions (e.g., FLEX, PRISMA). [ABSTRACT FROM AUTHOR]

BIM (building information modelling) has gained wider acceptance in the AEC (architecture, engineering, and construction) industry. Conversion from 3D point cloud data to vector BIM data remains a challenging and labour-intensive process, but particularly relevant during various stages of a project lifecycle. While the challenges associated with processing very large 3D point cloud datasets are widely known, there is a pressing need for intelligent geometric feature extraction and reconstruction algorithms for automated point cloud processing. Compared to outdoor scene reconstruction, indoor scenes are challenging since they usually contain high amounts of clutter. This dataset comprises the indoor point cloud obtained by scanning four different rooms (including a hallway): two office workspaces, a workshop, and a laboratory including a water tank. The scanned space is located at the Electrical and Computer Engineering department of the Faculty of Engineering of the University of Porto. The dataset is fully labelled, containing major structural elements like walls, floor, ceiling, windows, and doors, as well as furniture, movable objects, clutter, and scanning noise. The dataset also contains an as-built BIM that can be used as a reference, making it suitable for being used in Scan-to-BIM and Scan-vs-BIM applications. For demonstration purposes, a Scan-vs-BIM change detection application is described, detailing each of the main data processing steps. Dataset:  https://doi.org/10.5281/zenodo.7948116 Dataset License: Creative Commons Attribution 4.0 International License (CC BY 4.0). [ABSTRACT FROM AUTHOR]

Sediment Barriers (SBs) are crucial for effective erosion control, and understanding their capacities and limitations is essential for environmental protection. This study compares the accuracy and effectiveness of Terrestrial Laser Scanning (TLS) and Robotic Total Station (RTS) techniques for quantifying sediment retention in SBs. To achieve this, erosion tests were conducted in a full-scale testing apparatus with TLS and RTS methods to collect morphological data of sediment retention surfaces before and after each experiment. The acquired datasets were processed and integrated into a Building Information Modeling (BIM) platform to create Digital Elevation Models (DEMs). These were then used to calculate the volume of accumulated sediment upstream of the SB system. The results indicated that TLS and RTS techniques could effectively measure sediment retention in a full-scale testing environment. However, TLS proved to be more accurate, exhibiting a standard deviation of 0.41 ft3 in contrast to 1.94 ft3 for RTS and more efficient, requiring approximately 15% to 50% less time per test than RTS. The main conclusions of this study highlight the benefits of using TLS over RTS for sediment retention measurement and provide valuable insights for improving erosion control strategies and sediment barrier design. [ABSTRACT FROM AUTHOR]

The construction industry requires comprehensive and accurate as-built information for a variety of applications, including building renovations, historic building preservation and structural health monitoring. Reality capture technology facilitates the recording of as-built information in the form of point clouds. However, the emerging development trends of scan planning and multi-technology fusion in point cloud acquisition methods have not been adequately addressed in research regarding their effects on point cloud registration quality and data quality in the built environment. This study aims to extensively investigate the impact of scan planning and multi-technology fusion on point cloud registration and data quality. Registration quality is evaluated using registration error (RE) and scan overlap rate (SOR), representing registration accuracy and registration coincidence rate, respectively. Conversely, data quality is assessed using point error (PE) and coverage rate (CR), which denote data accuracy and data completeness. Additionally, this study proposes a voxel centroid approach and the PCP rate to calculate and optimize the CR, tackling the industry's challenge of quantifying point cloud completeness. [ABSTRACT FROM AUTHOR]

Terrestrial laser scanners (TLSs) are a standard method for 3D point cloud acquisition due to their high data rates and resolutions. In certain applications, such as deformation analysis, modelling uncertainties in the 3D point cloud is crucial. This study models the systematic deviations in laser scan distance measurements as a function of various influencing factors using machine-learning methods. A reference point cloud is recorded using a laser tracker (Leica AT 960) and a handheld scanner (Leica LAS-XL) to investigate the uncertainties of the Z+F Imager 5016 in laboratory conditions. From 49 TLS scans, a wide range of data are obtained, covering various influencing factors. The processes of data preparation, feature engineering, validation, regression, prediction, and result analysis are presented. The results of traditional machine-learning methods (multiple linear and nonlinear regression) are compared with eXtreme gradient boosted trees (XGBoost). Thereby, it is demonstrated that it is possible to model the systemic deviations of the distance measurement with a coefficient of determination of 0.73, making it possible to calibrate the distance measurement to improve the laser scan measurement. An independent TLS scan is used to demonstrate the calibration results. [ABSTRACT FROM AUTHOR]

Fouling organisms reduce a ship's fuel efficiency and disturb the ecosystem. Therefore, the International Maritime Organization (IMO) and many nations have enacted laws that mandate periodic hull cleaning for removing fouling organisms. However, cleaning niche areas of the ship hull is extremely difficult. Due to their complex shape, applying antifouling paint and cleaning with hull cleaning robots is difficult, but about 80% of fouling organisms are concentrated in the niche areas. To resolve this issue, this research proposes the use of an autonomous cleaning robot with a hydraulic polyarticular robot arm to clean niche areas of the ship hull. This robot can approach niche areas of the ship hull with complex shapes using its polyarticular arm. It was designed to be able to scan the cleaning area, establish a cleaning plan, and clean accordingly. This robot autonomously cleaned a propeller blade, which is a typical niche area of the ship hull, to verify the applicability of this system. The experiment results show that approximately 80% of the biofouling was removed from the hull crevices and 81% of the cleaned biofouling was recovered. [ABSTRACT FROM AUTHOR]