Search

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.

[EN] Precise documentation is essential to carry out the restoration and enhancement processes of protected heritage contexts. Data collection has been increasingly perfected, to the point of being able to perform virtual recreations of complex historical sites, in order to carry out in-depth studies and analyses. An example is Carcabuey Castle (Cordoba, Andalusia), a large fortress with important medieval structures. It is a monumental site of the so-called "Frontier Castles", which were located between the Kingdom of Aragon, and the Nasrid Kingdom of Granada. With the aim of restoring it and highlighting its value, an in-depth study was developed for its conservation and subsequent intervention. The data collection included terrestrial laser scanning and vectorising all the structures, as well as a complex and complete photogrammetric survey. From these previous data and carrying out a deductive analytical methodology, a model was generated which, after being printed in 3D (different models at different scales of detail), would allow the volumes, materials and textures which make up the castle, to be studied. The multidisciplinary team, composed of architects, archaeologists, historians and engineers, made it possible to provide multifaceted and inclusive character to all the work, both in the study of pathologies based on the models, and in the construction phases, detected by the stereotomy of the ashlars, or chemical composition of mortars. Since then, with all the data obtained in the research, summarised in this article, it has been possible to carry out a correct diagnosis for the restoration and enhancement of the heritage site. Highlights: High-definition scanning and 3D printing have been used as tools in the detection of heritage pathologies, as well as in the study of materials. The Carcabuey castle has been digitized and the volumetric data recovered from the study of its materials typology and its stereotomy, obtained with laser scanning. The study of construction and material phases, and the pathologies produced by them, has been carried out from the 3D printing of the heritage structure parts., [ES] La documentación precisa es fundamental para poder llevar a cabo los procesos de restauración y puesta en valor de los contextos patrimoniales protegidos. La toma de datos cada vez se ha ido perfeccionando más hasta el punto de poder realizar de forma virtual recreaciones de conjuntos históricos complejos para poder llevar a cabo profundos estudios y análisis. Un ejemplo de ello es el Castillo de Carcabuey (Córdoba, Andalucía), una gran fortaleza con importantes estructuras emergentes de época medieval. Se trata de un conjunto monumental de los llamados Castillos de Frontera que se ubicaban entre el reino de Aragón y el reino nazarí de Granada. Con el objetivo de restaurarlo y realzar su valor, se llevó a cabo un profundo estudio para su conservación y posterior intervención. La toma de datos consistió en el escaneado láser terrestre y vectorizado de todas las estructuras, así como en un complejo y completo levantamiento fotogramétrico. A partir de estos datos previos y llevando a cabo una metodología analítico-deductiva, se generó un modelado que permitiría, tras ser impreso en 3D (diferentes modelos a diferentes escalas de detalle), estudiar los volúmenes, materiales y texturas que configuran el castillo. El equipo multidisciplinar compuesto por arquitectos, arqueólogos, historiadores e ingenieros, permitió dar un carácter poliédrico e inclusivo a todo el trabajo, tanto de estudio de patologías a partir de los modelos, como de las fases constructivas detectadas por la estereotomía de los sillares o composición química de morteros. A partir de este momento, con todos los datos obtenidos en la investigación sintetizada en este artículo, se ha podido llevar a cabo una correcta diagnosis para la restauración y puesta en valor del conjunto patrimonial.

Statement of problem The anatomic complexity of the ear challenges conventional maxillofacial prosthetic rehabilitation. The introduction of specialized scanning hardware integrated into computer-aided design and computer-aided manufacturing (CAD-CAM) workflows has mitigated these challenges. Currently, the scanning hardware required for digital data acquisition is expensive and not readily available for prosthodontists in developing regions. Purpose The purpose of this virtual analysis study was to compare the accuracy and precision of 3-dimensional (3D) ear models generated by scanning gypsum casts with a smartphone camera and a desktop laser scanner. Material and methods Six ear casts were fabricated from green dental gypsum and scanned with a laser scanner. The resultant 3D models were exported as standard tessellation language (STL) files. A stereophotogrammetry system was fabricated by using a motorized turntable and an automated microcontroller photograph capturing interface. A total of 48 images were captured from 2 angles on the arc (20 degrees and 40 degrees from the base of the turntable) with an image overlap of 15 degrees, controlled by a stepper motor. Ear 1 was placed on the turntable and captured 5 times with smartphone 1 and tested for precision. Then, ears 1 to 6 were scanned once with a laser scanner and with smartphones 1 and 2. The images were converted into 3D casts and compared for accuracy against their laser scanned counterparts for surface area, volume, interpoint mismatches, and spatial overlap. Acceptability thresholds were set at 0.70 for spatial overlap. Results The test for smartphone precision in comparison with that of the laser scanner showed a difference in surface area of 774.22 ±295.27 mm2 (6.9% less area) and in volume of 4228.60 ±2276.89 mm3 (13.4% more volume). Both acceptability thresholds were also met. The test for accuracy among smartphones 1, 2, and the laser scanner showed no statistically significant differences (P>.05) in all 4 parameters among the groups while also meeting both acceptability thresholds. Conclusions Smartphone cameras used to capture 48 overlapping gypsum cast ear images in a controlled environment generated 3D models parametrically similar to those produced by standard laser scanners.

A 3D laser scanning strategy based on cascaded deep neural network is proposed for the scanning system converted from 2D Lidar with a pitching motion device. The strategy is aimed at moving target detection and monitoring. Combining the device characteristics, the strategy first proposes a cascaded deep neural network, which inputs 2D point cloud, color image and pitching angle. The outputs are target distance and speed classification. And the cross-entropy loss function of network is modified by using focal loss and uniform distribution to improve the recognition accuracy. Then a pitching range and speed model are proposed to determine pitching motion parameters. Finally, the adaptive scanning is realized by integral separate speed PID. The experimental results show that the accuracies of the improved network target detection box, distance and speed classification are 90.17%, 96.87% and 96.97%, respectively. The average speed error of the improved PID is 0.4239°/s, and the average strategy execution time is 0.1521 s. The range and speed model can effectively reduce the collection of useless information and the deformation of the target point cloud. Conclusively, the experimental of overall scanning strategy show that it can improve target point cloud integrity and density while ensuring the capture of target.

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%).

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.

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.

Laser ultrasonic techniques (LUTs) are becoming widely used for damage detection based on full-field ultrasonic data. In general, LUTs provide threedimensional (3-D) ultrasonic signals from which significant informative features may be extracted about the health condition of a structure. In this paper, statistical convariance method is proposed to investigate 3-D ultrasonic features. A laser ultrasonic interrogation method based on a Q-switched laser scanning system was used to interrogate 3-D ultrasonic signals in to a 2 mm aluminum plate. The ultrasonic signals in three-dimensional (3-D) space were generated, indexed by spatial N (xdirection), spatial M (y-direction), and temporal K (t-direction) samples, respectively. Then, two sets of covariance matrices were obtained based on the vector variables in x-direction and y-direction respectively for all k time samples respectively. The covariance imaging and the corresponding variance map were obtained. The wavelength and group velocity of S0 and A0 modes were able estimated from the variance map. The wavelength of the S0 and A0 modes were estimated with the deviation error of 2.3% and 11% respectively. The group velocities of S0 and A0 modes were estimated with the deviation error of 1.8% and 0.9%. The analysis will be further performed to develop group velocity curves for a range of frequency in metal and composite plates.

Quality control in industry involves trained operators to manipulate and inspect metallic surfaces in order to identify, and eventually correct, manufacturing defects. These tasks are manually performed, and a poor performance (e.g., missing defects) leads to an increase of the costs and prolongation of the manufacturing time cycle. In this work, we propose a multi-agent robotic platform to autonomously perform Industry 4.0 quality control processes of metallic surfaces. The platform consists of three anthropomorphic robots with custom-made end-effectors designed to manipulate, inspect, and eventually correct a metallic frame of a motorcycle. The description of a novel multi-agent platform is followed by the presentation of the developed inspection procedure, in which a linear laser scanner is used to reconstruct the three-dimensional metallic surface of a motorcycle with a resolution of ~0.1 mm. In order to validate the platform, we perform a set of experiments to assess the performance of the robotic platform in a real Industry 4.0 scenario. Results confirmed that such a system guarantees a sub-millimetric precision to identify defects on complex-shaped metallic surfaces and effectively correct them. The proposed robotic platform can be adopted for overcoming the drawbacks of a traditional procedure that relies on visual-tactile manual defects correction (e.g., low-repeatability, high-subjectivity) and is scalable to different industrial applications. The proposed approach aims to elevate the role of operators to expert supervisors of the process, limiting the interactions with potentially-dangerous tools/procedures and thus improving the working conditions in an industrial 4.0 scenario.

Xinglinpu Bridge was built on the S3801 freeway in 2019 in preparation for the winter Olympics in Beijing, China. It is a cable-stayed steel bridge with pylons in the shape of flower baskets. Using Xinglinpu Bridge as a case study, a systematic approach to the dimensional quality assessment of complex bridges using a combination of three-dimensional (3D) point clouds obtained by terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) surveys is proposed in this paper. The currently available methods for dimensional quality assessment of complex bridges rely largely on manual inspection and contact-type measurement devices, which are time consuming and costly. To overcome these limitations, this paper presents a framework for dimensional quality assessment composed of three parts: scanning schemes for TLS and UAV, scanning implementation and measurement of geometric dimensions. The results of configuration detection verified the high-quality construction of Xinglinpu Bridge, although millimetre-scale differences were obtained between the point clouds and the design value. The potential and limitations of 3D laser scanning for assessing the quality of complex bridges are discussed.

The high corrosion resistance, low density, and useful biological activity with heat resistance of titanium alloys have made them the most outstanding choice in various industrial applications. However, their poor tribological properties inhibit utilizing them in applications that need abrasive and adhesive wear resistance. Laser cladding is being applied to increase the capabilities of such alloys by allowing the deposition of different hard coating materials. This paper attempts to study the thermal, microstructure, and clad layer geometry evolution during coaxial laser cladding of Ti6Al4V titanium alloy with tungsten carbide + nickel-based alloy preblended powder. Owing to the difficulty in experimentally measuring the thermal and microstructure evolution due to lots of laser processing parameters, a new three-dimensional numerical model based on finite-difference analysis for studying the entire process has been proposed. The behavior of the different thermophysical properties of WC, NiCrBSiC, and Ti6Al4V materials, as well as the phase transition based on latent heat and fluid dynamics considering materials velocity, viscosity, and buoyancy force, during melting and resolidification processes, were considered to improve and ensure the accuracy of the numerical model. The proposed model could be applied to accurately estimate the temperature history and the deposited clad layer morphology and geometry. The cooling rate and thermal gradient were investigated to predict the solidification rate and microstructure by using different laser cladding parameters. It was confirmed that the laser power has a substantial impact on the peak temperature in the melt-pool, while the laser scanning speed has a significant effect on the heating and cooling rates. In conclusion, the process parameters have to be carefully chosen to certify a good quality clad layer with the preservation of the WC particles.

Fabrication of the surface micro-texture on the C-plane sapphire is undertaken by a 355 nm Ultraviolet (UV) pulsed laser. The surface micro textures of sapphire with different laser scanning line spacing ranging from 10 μm to 100 μm are obtained, where the selection range of scanning line spacing is controlled in the range of the groove width and plasma width to obtain a surface of high Peak-Valley (PV) value. A reasonable processing order is proposed to manufacture different types of surface micro-textures on sapphire by laser ablation trajectory regulation. In the multiple-passes laser ablation of sapphire by the UV nanosecond pulsed laser, the scanning lines in each direction is treated as once scanning. On this basis, the multiple processing can be carried out to avoid the influence of the subsequent scanning on the machined groove. In addition, the effect of different scanning line spacing on the PV value is quantified and different types of surface micro-textures on sapphire, including the squares, the rhombuses and the hexagons, are successfully fabricated, which can be applied in the friction reduction or anti-reflection field.

Semi- and nonparametric models are popular in the area-based approach (ABA) using airborne laser scanning. It is unclear, however, how many predictors and training plots are needed to provide accurate predictions without overfitting. This work aims to explore these limits for various approaches: ordinary least squares regression (OLS), generalized additive models (GAM), least absolute shrinkage and selection operator (LASSO), random forest (RF), support vector machine (SVM), and Gaussian process regression (GPR). We modeled timber volume (m3·ha–1) for four boreal sites using ABA with 2–39 predictors and 20–500 training plots. OLS, GAM, LASSO, and SVM overfitted as the number of predictors approached the number of training plots. They required ≥15 plots per predictor to provide accurate predictions (RMSE ≤30%). GAM required ≥250 plots regardless of the number of predictors. The number of predictors only mildly affected RF and GPR, but they required ≥200 and ≥250 training plots, respectively. RF did not overfit in any circumstances, whereas GPR overfit even with 500 training plots. Overall, using up to 39 predictors did not generally result in overfit, and for most model types, it resulted in better accuracy for sufficiently large datasets (≥250 plots).

Accurate real-time positioning in forests is challenging due to GNSS signal degradation and an unstructured spatial environment that is difficult to conceptualize through visual sensing. Positioning is vital in any forestry automation application, such as collecting inventory, harvesting, or search and rescue missions. Lidar and inertial based solutions are popular, however they often obtain real-time computation by effectively compressing the number of measurement points to track utilizing regular geometric shapes that do not adapt well to forest. Other solutions sacrifice the high-frequency of positioning estimates or they rely on post-processing. We propose a real-time lidar-inertial SLAM-based approach that utilizes NDT scan registration, factor graphs and loop closure corrections to produce accurate and high-frequency pose estimates. To test our method, data was captured with a lidar and imu sensor mounted on a stick surveying forest sites. Ground truth trajectory for accuracy evaluation was computed by fine registering individual laser scans onto a high-quality reference point cloud recorded from the same forest area using terrestial and airborn laser scanning methods. Experiments shows, that our method can produce real-time position estimates up to 200 Hz within 2–15 cm error.

U památkových objektů (a nejen u nich) je často problémem neexistující či neaktuální výkresová dokumentace. V posledních letech se namísto tradičního zaměřování objektů s pomocí jednodimenzionálních pomůcek (ať už máme na mysli pásmo či laserový dálkoměr) pomalu prosazuje třídimenzionální zaměřování pomocí laserového skenování, při kterém je vytvořena virtuální prostorová kopie objektu za pomoci milionů bodů, tzv. mračna bodů. Toto mračno či mračna můžeme použít k tvorbě 2D i 3D dokumentace stávajícího stavu objektu s mnohem větší rychlostí, přesností i přehledností, než je tomu u klasických metod. V současné době jsou nejrozšířenější dvě metody laserového skenování s využitím tzv. LIDARu – statická metoda, využívající pevných stanovišť a dynamická metoda, využívající moderní technologie v podobě přesných IMU jednotek. Článek popisuje princip těchto dvou metod, jejich výhody a nevýhody a také způsob práce s takto vytvořenými mračny bodů. Většímu rozšíření takto vytvořených virtuálních reprezentací skutečných objektů bohužel brání vyšší pořizovací cena potřebných přístrojů, již dnes je však jejich cena násobně nižší než v nedávné minulosti a v dohledné budoucnosti by snad mohly být dostupné všem, kdo by je při své činnosti potřeboval. V článku jsou také příklady mračen bodů i ukázky výstupů, které díky nim vznikly. In the case of heritage buildings (and not only in their case), the problem is often the absence or outdated drawing documentation. In recent years, instead of the traditional surveying of buildings with the help of onedimensional tools (whether we mean a tape measure or a laser rangefinder), three-dimensional surveying using laser scanning, in which a virtual spatial copy of the object is created with the help of millions of points, the so-called point cloud, has been slowly gaining ground. This cloud or clouds can be used to create 2D and 3D documentation of the existing state of the building with much greater speed, accuracy and clarity than conventional methods. Currently, the two most widely used methods of laser scanning using so-called LIDAR are the static method, using fixed stations, and the dynamic method, using modern technology in the form of precision IMUs. The paper describes the principle of these two methods, their advantages and disadvantages and also the way of working with point clouds created in this way. Unfortunately, the greater spread of virtual representations of real objects created in this way is hindered by the higher purchase price of the necessary instruments, but already today their cost is many times lower than in the recent past and in the foreseeable future they could hopefully be available to all who would need them in their activities. The article also includes examples of point clouds as well as examples of the outputs they have produced.

Glavni cilj magistrske naloge je bila raziskava obdelave in združevanja oblakov točk mobilnega (MLS) in aerolaserskega skeniranja (ALS). Z združevanjem oblakov MLS in ALS dobimo večje število informacij o skeniranem okolju in se izognemo določenim pomanjkljivostim vsakega od sistemov. Združen oblak točk pokriva celotno skenirano površje razen atrijev, ki jih z nobenim od sistemov ne moremo doseči. Najprej smo raziskali različne možnosti registracije oblakov točk MLS v programu Terrasolid in na testnem območju na osnovi odstopanj na kontrolnih točkah določili najboljši postopek. Oblaku točk MLS smo nato dodali oblak točk ALS in dobili združen oblak točk. Za avtomatsko modeliranje stavb iz združenega oblaka točk MLS in ALS na trgu nismo našli ustreznega programa, zato smo v programu Terrasolid na avtomatski način izdelali modele stavb le iz oblaka točk ALS. Nato smo na primeru izbrane kompleksnejše stavbe iz združenega oblaka točk ročno izdelali njen model, ki smo ga z vidika natančnosti in podrobnosti primerjali z avtomatsko izdelanim modelom. Na koncu v obliki razprave povzamemo težave pri zajemu in obdelavi podatkov, združevanju oblakov točk MLS in ALS ter modeliranju stavb. The main goal of the master's thesis was to research the processing and merging of point clouds from mobile (MLS) and airborne laser scanning (ALS). By merging MLS and ALS point clouds, we obtain more information about the scanned environment and avoid certain limitations of each system. The merged point cloud covers the entire scanned surface except for atriums, which cannot be reached by either of the systems. Initially, we explored various options for registration of MLS point clouds in the Terrasolid software and determined the best process based on deviations at control points in a test area. We then added ALS point clouds to the MLS point cloud to obtain the merged point cloud. We did not find an appropriate program for automatic building modeling from the merged MLS and ALS point cloud on the market, so we used Terrasolid to automatically create building models only from the ALS point cloud. We manually created the model of a selected complex building from the merged point cloud and compared its accuracy and detail with the automatically created model. Finally, in the form of a discussion, we summarized the problems with data acquisition and processing, merging MLS and ALS point clouds, and building modeling.

Terestrično lasersko skeniranje, ki zajema podatke na osnovi merskega sistema lidar, velja za eno novejših tehnologij zajema podatkov na področju geodezije. Oprema za skeniranje je relativno draga, sam proces zajema in nadaljnja obdelava pa zahtevata veliko inženirskega znanja, zato se lasersko skeniranje uporablja le za specifične naloge s področja geodezije, gradbeništva, arheologije, arhitekture in podobno. Razvoj in minituarizacija senzorjev ter mikroprocesorjev omogočata vse večjo dostopnost lidar merskih sistemov, s tem pa se lasersko skeniranje približa širšim uporabnikom. Podjetje Apple je bilo leta 2020 prvo, ki je v svoje pametne naprave vgradilo sistem senzorjev lidar, tako pa je lasersko skeniranje tudi prvič pristalo v rokah laičnega uporabnika. V sklopu magistrske naloge preverjamo kako se nizkocenovni laserski skener, vgrajen v tablični računalnik Apple, odreže v primerjavi s profesionalnim geodetskim terestričnim laserskim skenerjem. Zanima nas morebitna uporabnost prvega za naloge na področju geodezije. Terrestrial laser scanning, which collects data based on the lidar measurement system, is considered one of the newer technologies for data collection in the field of geodesy. The scanning equipment is relatively expensive and the acquisition process itself, as well as further processing require a lot of technical knowledge, so laser scanning is only used for special tasks in the fields of geodesy, civil engineering, archaeology, architecture and the like. The development and miniaturisation of sensors and microprocessors enables the increasing accessibility of lidar measurement systems and brings laser scanning closer to a wider range of users. In 2020, Apple became the first company to integrate a lidar sensor system into its smart devices, making laser scanning accessible to laypeople for the first time. In this paper, we investigate how a low-cost laser scanner built into an Apple device compares to a professional geodetic terrestrial laser scanner. We are interested in the potential applicability of the former for geodetic tasks.

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.

Both drones and laser scanners digitally take the as-built context of an object into the computer and the data taken is transmitted to a Building Information Modeling (BIM) world to create ac-curate 3D models. Although the laser scanner is the leading method of the Scan-to-BIM proce-dure, many professionals indicate drawbacks of the technology and point out the drone is an al-ternative that can improve the shortcomings, leading to the UAV-to-BIM process. Korean con-struction industry plans to implement the drone technology for scrutinizing as-built construc-tion quality by 2025. However, the drone is not popular in the construction projects. Korean universities where Construction Engineering and Management program have been implement-ed are requested to develop a drone curriculum for construction professionals. Since the majori-ty of the professionals are not familiar with drone operation, in order for the schools to be suc-cessful in developing the curriculum, it is very necessary to perform a preliminary experimental study for identifying the essential education contents that are appropriate to drone beginners. The main objective of this paper is to perform the study for the drone beginners and recognize the recommendations and the framework of drone curriculum that will be beneficial for the schools to develop a comprehensive curriculum later on.

Medical treatments such as high-intensity focused ultrasound, hyperthermic laser lipolysis or radiofrequency are employed as a minimally invasive alternatives for targeted tissue therapies. The increased temperature of the tissue triggers various thermal effects and leads to an unavoidable damage. As targeted tissues are generally located below the surface, various approaches are utilized to prevent skin layers from overheating and irreparable thermal damages. These procedures are often accompanied by cooling systems and protective layers accounting for a non-trivial detection of the subsurface temperature peak. Here, we show a temperature peak estimation method based on infrared thermography recording of the surface temperature evolution coupled with a thermal-diffusion-based model and a time-dependent data matching algorithm. The performance of the newly developed method was further showcased by employing hyperthermic laser lipolysis on an ex-vivo porcine fat tissue. Deviations of the estimated peak temperature remained below 1 °C, as validated by simultaneous measurement of depth temperature field within the tissue. Reconstruction of the depth profile shows a good reproducibility of the real temperature distribution with a small deviation of the peak temperature position. A thermal camera in combination with the time-dependent matching bears the scope for non-contact monitoring of the depth temperature profile as fast as 30 s. The latest demand for miniaturization of thermal cameras provides the possibility to embed the model in portable thermal scanners or medical laser technologies for improving safety and efficiency.

Airborne laser scanning (ALS) technology is fully implemented in forest resource assessment processes, providing highly accurate and spatially continuous results throughout the area of interest, thus reducing inventory costs when compared with traditional sampling inventories. Several approaches have been employed to estimate forest parameters using ALS data, such as the Area-Based Approach (ABA) and Individual Tree Crown (ITC). These two methodologies use different information processing and field data collection approaches; thus, it is important to have a selection criterion for the method to be used based on the expected results and admissible errors. The objective of this study was to compare the prediction errors of forest inventory attributes in the functioning of ABA and ITC approaches. A plantation of 500 ha of Pinus radiata (400–600 trees ha−1) in Chile was selected; a forest inventory was conducted using the ABA and ITC methods and the accuracy of both methods was analyzed. The ITC models performed better than the ABA models at low tree densities for all forest inventory attributes (15% MAPE in tree density—N—and 11% in volume—V). There was no significant difference in precision regarding the volume and basal area (G) estimations at medium densities, although ITC obtained better results for density and dominant height (Ho). At high densities, ABA performed better for all the attributes except for height (6.5% MAPE in N, 8.7% in G, and 8.9% in V). Our results showed that the precision of forest inventories based on ALS data can be adjusted depending on tree density to optimize the selected approach (ABA and ITC), thus reducing the inventory costs. Hence, field efforts can be greatly decreased while achieving better prediction accuracies.

A combination of systematic and bibliometric literature review is applied. For bibliometric analysis a citation network analysis, keyword cluster analysis, burst detection analysis and the total citation score are evaluated. So far, literature mainly deals with creation of digital building models. However, in the operational phase of a building, updating digital building models is essential in order to use the digital building models for applications like maintenance, facility management and conversion planning. In this paper approaches and methods to update digital building data are examined systematically to reflect the current state of scientific knowledge. This will identify and compare update approaches for digital building models. Nine interrelated research areas can be identified that deal with updating digital building information. Based on the body of knowledge on the topic "Updating of digital building models", research gaps and poorly represented research areas are identified. One gap in research is the use of photogrammetry to update individual buildings during their operational phase. In addition to strong research areas such as geoscience, which has produced update approaches over the years, areas like factory planning have been identified which hardly consider approaches to updating as-built data. Only the most important and largest research areas involved have been considered. A more detailed examination would be possible, but would go beyond the scope of this paper. This paper is the first to analyse updating approaches in a detailed, systematic, and bibliographic manner. The holistic view of the topic of updating approaches of digital building models helps to get an overview of existing approaches. Especially because in building operation up-to-date digital plan documents of the building are increasingly needed, this overview is necessary.

Developing accurate and efficient measurement systems for blade profiles has always been a vital issue in blade manufacturing. Nowadays, optical-based systems for measuring blade profiles have attracted significant interest due to their high efficiency and flexibility. However, as key steps in optical measurement of blades, system calibration and establishment of measurement datum are normally accomplished based on calibration objects, which may introduce uncertainty and affect the accuracy of the measurement. In this article, we propose a novel method for blade-profile measurement based on blade self-features. A measurement system based on a four-axis platform and laser scanning sensor (LSS) is developed. A calibration method based on the blade datum plane feature is introduced to eliminate the pose error of the system without using additional calibration objects. A feature-matching algorithm based on the covariance matrix of the blade local leading-edge feature is further proposed to establish the measurement datum. The proposed method requires smaller system-motion space and fewer LSS viewpoints, which would improve the efficiency and flexibility of the measurement system. Furthermore, less error accumulation can be achieved using our method, thus, resulting in higher measurement accuracy. The experimental results reveal the feasibility and good practical application prospect of this method.

Ti6Al4V is one of the most widely used titanium alloys due to its excellent mechanical, physical, and chemical properties. Laser surface texturing is a promising method to endow new functions of material surfaces; however, direct generation of laser-induced periodic surface structure (LIPSS) on the Ti6Al4V surface by nanosecond laser is rarely reported. In this study, by nanosecond laser irradiation in nitrogen atmosphere, the ripples (a typical LIPSS) were directly fabricated on the Ti6Al4V surface. By single-line laser scanning, the effects of laser irradiation parameters including the laser power and repetition frequency on the formation and evolution of the ripples were systematically investigated, followed by optimizing the laser irradiation parameters to achieve the large-area regular and clear ripples with relatively good surface quality as well. Furthermore, by performing contrast experiments in argon atmosphere, the role of nitrogen atmosphere on the formation of ripples was confirmed. Accordingly, formation mechanism of the ripples was discussed. Finally, the effects of the formed ripples on the surface color and wettability were preliminarily characterized to demonstrate the potential applications of surface ripples. This paper provides a nitrogen assisted method to fabricate large-area ripples on the Ti6Al4V surface by nanosecond laser irradiation.

Fabrication of thin-wall components using the laser powder bed fusion (LPBF) additive manufacturing (AM) technology was investigated for two “hard-to-weld” high gamma prime Ni-based superalloys RENE 65 (R65) and RENE 108 (R108). Simple block parts with wall thicknesses of 0.25 mm, 1.00 mm, and 5.00 mm are printed using a bidirectional laser scanning strategy without layer-wise rotation. Parts with walls thinner than 5 mm fail before reaching the designated build height. Results indicate that reduction of limiting build height (LBH) corresponds to the reduction of part thickness and is unaffected by alloy composition. On the contrary, the number of internal micro-cracks along columnar grain boundaries in the build direction (BD) increases with part thickness and is significantly higher in R108 than R65. These findings suggest that reduced LBH in parts with thinner walls is not caused by internal micro-crack formation. Fractography and finite element analysis (FEA) of the in-process thermal stresses show that the LBH trend is not explained by the conventional cracking mechanism. Simulations suggest that part thickness affects stress distribution leading to more substantial distortion and consequent failure to add layers for continued fabrication of thinner parts.

Laser-induced controllable oxidation coupled with micro-milling (LOMM) provides a feasible way to machine difficult-to-machine materials such as TiB2–TiC ceramic composites. The oxidation mechanism of the material under laser irradiation represents the fundamental issue of LOMM. In this paper, laser-induced controllable oxidation of spark plasma sintered TiB2–TiC ceramic composites as the workpiece material was studied. A three-dimensional finite element model was established based on ABAQUS/CAE 6.14 software to simulate the effect of laser parameters on temperature field distribution and was verified by experiments. The influence of laser processing parameters and assisted gas atmospheres on the oxidation behavior of TiB2–TiC ceramic composites was investigated. Results revealed that the irradiated temperature which had a significant impact on oxidation behavior, increased with an increment of the laser fluence and decreased with an increment of scanning speed with other laser parameters fixed. In addition, based on experimental analysis, the thickness of the oxide-layer increased with an increase of laser fluence and reduced with increasing laser scanning speed. At a laser fluence of 10.78J/cm2 and scanning speed of 1 mm/s as well as in an oxygen-rich atmosphere, a loose and porous oxide-layer was produced on the irradiated surface. Cross-section thicknesses of the oxide-layer and sub-layer reached 63 μm and 22 μm, respectively. Moreover, the thickness of the oxide-layer was 22 μm in air surroundings and hardly be found in argon and nitrogen atmospheres under identical laser parameters, which indicated that oxygen content had a significant influence on the oxidation reaction of the material. The products of the oxide-layer were mainly composed of rutile- and anatase-TiO2. Furthermore, the hardness of the sub-layer was 9.6 ± 0.7 GPa at a laser fluence of 10.78J/cm2 and scanning speed of 1 mm/s, which was far lower than that of the substrate with a hardness of 20 ± 0.7 GPa. This study provides a theoretical basis for subsequent micro-milling.

There are many approaches to address geospatial monitoring of pipeline overpasses, among which the most widespread methods are terrestrial laser scanning and total station measurements. However, there is a problem in comparing the geospatial monitoring data collected by different methods in different epochs. The main task of this work is to find the correspondence between points in different epochs. The total station measurements are carried out in specific discrete points of the pipeline overpass. In contrast, terrestrial laser scanning allows the collection of the whole data set without fixing specific point coordinates. In order to compare different data in different epochs, it is necessary to select a relevant presentation of the monitoring results (reference model) and specify appropriate criteria for quality inspection. In general, a pipeline can be presented as a spatial curve. In this study, two types of reference models are considered: cubic splines and Bezier curves. These models are examined for the monitoring of two gas pipeline overpasses. The first measurement epoch is accomplished by the terrestrial laser scanning, and the second measurement epoch is completed by the total station. The reference models are simulated by Matlab coding. The preliminary accuracy of ground laser scanning and total station measurement is selected as the criterion of quality inspection. The simulation and comparison results provide the evidence that the correct selection of reference model is a crucial component of successful geospatial monitoring. The results show that the Hermite splines are effective in the comparison of different data sets. These splines present the interpolation accuracy compatible with measurement accuracy, i.e., 15–20 mm for spatial displacement determination.

To improve the quality of narrow overlap welds and reduce cost during the high-strength production, it is essential to detect weld defects promptly by identification of the type of defects to provide solution accordingly. This paper proposes an integrated weld defect identification approach combing eddy current detection with 3D laser scanning based on Convolutional Neural Networks (CNN). The detection principle and equipment of the two detection methods are introduced. To fit the training process of CNN, two set of detection signals are preprocessed: a two-dimensional time-frequency diagram for eddy current signals using continuous wavelet transform and for laser images, weld edges are extracted and divided by region using image convolution and combining with integral graph. CNN model VGG16 is trained afterwards with data collected from one local manufacturer in Shanghai. It is discovered that performance of eddy current and laser image identification on different types of weld defects is different, and the accuracy can be increased with the two methods combined. Last, to achieve real-time detection of narrow overlap welding, a two-stage defect recognition model is built which greatly improves the efficiency of weld defect identification without affecting the accuracy of weld defect identification.

The digitisation of heritage is being rapidly realised in many parts of the world thanks to LiDAR technology. In addition to the simple digital preservation of heritage, 3D acquisition makes it possible to monitor the structural condition and assess possible damage. This paper presents a method for modelling the lost volume of a heritage bridge. The selected case study is the Fillaboa bridge, in Salvaterra de Miño, Spain, which has two cutwaters with the same cutting angle, one of which is damaged and has a stone loss. The bridge was acquired with a Terrestrial Laser Scanner. The method consists of the following processes. First, the walls of the whole cutwater are segmented and aligned by Iterative Closest Point algorithm over the damaged cutwater. Second, the distance between the two point clouds is calculated and the damaged area is delimited in both point clouds. And third, the alpha shape algorithm is applied to model the point cloud of the damaged area to a polygon. By searching for the optimal alpha radius, the polygon that best fits the damaged volume is generated. The proposed method also allows digital reconstruction of the damaged area, although it is sensitive to acquisition problems, which require manual interventions in the processing. The accuracy of the method is mainly dependent on the acquired point cloud registration (with an RMS error of 60mm) and the ICP registration error (31mm). Its use is limited to the existence of two geometries that allow superposition: one in good condition and one damaged to compare.

The European building stock needs fast and affordable digitalization for facilitating the renovation process to achieve higher energy efficiency in buildings and in houses. Most of the residential buildings built between 1925-1975 lack proper documentation and digital building information, as opposed to newer buildings. Digital building information (geometry and attribute data) is required to plan retrofitting projects or renovations of facades. This work can only be efficient if Building Information Modelling (BIM) is available for stakeholders (owners, architects, contractors etc.). Whereas city planners of municipalities or social housing companies are striving to manage their properties and building portfolio on multiple scales, these stakeholders are seeking an approach that enables spatial planning, efficient asset management and energy consumption and management services for their buildings. In a EUREKA labelled project (E!12649 Ready2BIM) three partners worked together, two from Hungary (Geonardo Ltd. and SZTAKI) and one from Germany (CAALA GmbH).

The emerging technique of carbonization of polyimide (PI) by direct laser writing receives great attention for its flexibility, versatility, and ease-of-patterning capability in creating a variety of functional laser-induced graphene (LIG) sensors and devices. LIG prepared by CO2 laser irradiating of the PI film is characterized by scanning electron microscopy, X-ray diffraction (XRD), transmission electron microscope (TEM), specific surface area analyzer, synchronous thermal analysis, and Raman spectroscopy with the focus on investigating the effects of laser parameters (e.g. power, scanning speed) on the microstructure, thickness, and sheet resistance of LIG. Both TEM and XRD indicate that LIG is composed of many graphene layers with a layer spacing of 0.34 nm. The specific surface area of LIG decreases with the increase of laser power. The ratio of the thickness of LIG over the depth of the carbonized PI film as the expansion ratio characterizes the expansibility of LIG. The influence of laser scanning speed and off-focus value on the sheet resistance of LIG is explained by the superposition mechanism of laser scanning spots.

The edge effect is described as an unexpected bending angle variation along the scan line in the laser bending process. In this paper, an analytical model and finite element analysis of temperature fields and bending angles are used to obtain insight into the mechanism of edge effects in the laser bending process of DP980 high-strength steel. Based on the analysis of temperature distributions and influences of scanning velocity on edge effects, it is found that the edge effect of laser bending increases sharply with laser scanning velocity when the constant scanning velocity is smaller than 3 m/min. A varying velocity scanning strategy is proposed to reduce the edge effects of DP980 high-strength steel. By comparing the temperature distributions and bending angles between the varying velocity scanning and the constant one, it is confirmed that the relative bending angle variation in the varying velocity scanning strategy reduces by 54.1% compared to the constant one, which indicates that the varying velocity scanning strategy can significantly reduce the edge effect of the laser bending process. Simultaneously, the average bending angle of the steel sheet increases in the proposed new strategy, which indicates that forming efficiency is improved.

Correct measurement and qualification of failure mode for steel members are important for the development of member design methods, and have the potential to effectively identify the failure mechanisms of structures after disaster. Modern laser based geometric measurement technique can easily obtain 3D point clouds of member. However, rare studies have been reported on the deformation measurement from the geometric model reconstructed from 3D point clouds of an extensively deformed member. This study focuses on the automatic 3D geometric model reconstruction of steel column in failure state using the laser scanning technique and the qualification of the deformation. First, tests were carried out on steel I-columns subjected to axial compression to obtain two typical failure modes which were then transferred to 3D point clouds using the laser scanning technique. Afterwards, a rectangular coordinate system was built, and 3D point clouds were sliced into several cross-sections based on the plane-section assumption. The flanges and web were filtered out by applying thresholds to cross-correlation coefficient between the points’ normal and the unit vectors along the axes. A curve segmentation method using the image-based cross-correlation matching was proposed to accurately detect the corner points and weld regions in cross-section. The 3D geometric model was then reconstructed by assembling the cross-sections along the longitudinal axis of column. Finally, a cross-sectional constrained finite strip method (cFSM) was proposed based on the cross-sectional pure buckling modes generated using the classical cFSM method, which is more efficiency and robust. Both the proposed method and the classical cFSM method were used to qualify the deformation obtained from reconstructed 3D geometric model. Comparison of the qualification results between these two methods verified the validity of the proposed method.

Accurate measurement of forest growing stock is a prerequisite for implementing climate-smart forestry strategies. This study deals with the use of airborne laser scanning data to assess carbon stock at the tree level. It aims to demonstrate that the combined use of two unsupervised techniques will improve the accuracy of estimation supporting sustainable forest management. Based on the heterogeneity of tree height and point cloud density, we classified 31 forest stands into four complexity categories. The point cloud of each stand was further divided into three horizontal layers, improving the accuracy of tree detection at tree level for which we calculated volume and carbon stock. The average accuracy of tree detection was 0.48. The accuracy was higher for forest stands with lower tree density and higher frequency of large trees, as well as a dense point cloud (0.65). The prediction of carbon stock was higher with a bias ranging from –0.3% to 1.5% and a root mean square error ranging from 0.14% to 1.48%.

Multi-sensor data fusion has recently gained a wide attention within the Geomatics research community, as it helps overcome the limitations of a single sensor and enables a complete 3D model for the structure and a better object classification. This study develops a data fusion algorithm, which optimally combines sensor data from a terrestrial and an unmanned aerial system (UAS) to obtain an improved and a complete 3D mapping model of a structure. Terrestrial laser scanner (TLS) data are collected for the exterior of a building along with the DJI Phantom 4 Pro and terrestrial close-range Sony α7R camera images. A number of ground control points and targets are established throughout the scanned building for the photogrammetric process and scans registration. Different point cloud datasets are generated from the TLS, UAS and the terrestrial Sony camera images. The created point clouds from each individual sensor and the fused point clouds are used in different forms, namely the original, denoised and subsampled point clouds. The denoised point cloud dataset is generated through the application of the statistical outlier remover (SOR) filter on the original point clouds. The relative precision of the 3D models is investigated using the multiscale model-to-model cloud comparison (M3C2) method. The TLS-based 3D model is used as a reference. It is found that the precision of the Sony-based 3D model is higher than the other two models for the original and denoised datasets. The fused Sony/UAS-based model provides a complete 3D model with precision higher than the UAS-based model.

This paper presents a method to generate a Georeferenced 3D point cloud of GPS denied built structures using custom made backpack laser scanning system. An orthogonal combination of 2D Hokuyo laser scanners has been used on the backpack system to generate a 3D point cloud of the surveyed environments. The data logging of scanners and simultaneous localization and mapping (SLAM) of the scanning system have been carried out using Robot Operating System (ROS). The developed local SLAM based 3D point cloud solution has been transformed into global Georeferenced 3D point cloud using observed geographic coordinates of nearby GPS visible vicinities. Multiple indoor environments have been scanned and 3D point clouds have been developed which have been found accurate when compared to the ground truth. In comparison to available surveying solutions present in the local market, the developed system has been found more accurate, faster, and user friendly to generate structural results of the surveyed vicinities in detail. The efficacy of the system has been witnessed by local surveying companies by delivering the unique global coordinated solutions on affordable rates.

The determination of a fully populated variance-covariance matrix (VCM) of a point cloud acquired with a terrestrial laser scanner (TLS) is not straightforward as physical correlations between TLS observations are not sufficiently known. Ignoring correlations leads to biased estimates, wrong modeling of surfaces, or the misinterpretation of geometric changes. For this reason, this study aims at progressing the empirical determination of correlations in TLS range observations by investigating short-scale correlations (mm to cm) of TLS rangefinders. Therefore, two methods are proposed to determine spatial correlations between TLS range observations. Both methods are evaluated for simulated laser scans, and then applied to empirical data of four different terrestrial laser scanners. The results demonstrate that short-scale correlations exist, and it is possible to quantify the relevant parameters to fill the VCM. It also shows that the correlation differs between the scanners and with the distance. Furthermore, we analyze the change of the correlation length with changing scanning configurations such as distance, incidence angle, and reflectivity with the result that this must be considered while applying the aforementioned methods to point clouds of large objects. All in all, this study trustfully quantifies physical short-scale correlations yielding from the rangefinder and suggests a guideline to apply this to point clouds of large objects.

Visibility is a key factor influencing animal behavior in forest ecosystems. Fine-scale visibility in forested areas has been measured by ground-based approaches at the plot level, using site-specific methods that have limited spatial coverage. Here we examine airborne laser scanning (ALS) as a novel tool to quantify fine-scale visibility in the temperate forests of Germany at a landscape scale. We validate the (vertically-derived) ALS-derived visibility measures using proven (horizontally-derived) terrestrial laser scanning (TLS) estimates of true visibility. Our results indicate that there is a good agreement between the visibility resulting from ALS and TLS with an R2 ranging from 0.53 to 0.84 and a normalized RMSE varying from 15.92% to 11.81% at various plot sizes, with the highest accuracy achieved using a plot size of 35 × 35 m. Our study demonstrates for the first time that ALS can be successfully applied to quantify fine-scale visibility in temperate forests at a landscape level. This approach holds potential for studying the spatial behavior of animals (e.g., habitat selection and predator–prey relationships) in forest ecosystems.

This paper proposes a scanner–stage synchronized approach emphasizing a novel control structure for the laser polishing of Inconel 718 components manufactured by selective laser melting in order to address increasing demands for high surface quality in metal additive manufacturing. The proposed synchronized control system is composed of a motion decomposition module and an error synthesis module. The experimental results show that stitching errors can be avoided thanks to continuous motion during laser processing. Moreover, in comparison with the existing step-scan method, the processing efficiency of the proposed method is improved by 38.22% and the surface quality of the laser-polished area is significantly enhanced due to a more homogeneous distribution of the laser energy during the material phase change. The proposed synchronized system paves the way for high-speed, high-precision, and large-area laser material processing without stitching errors.

Modelling of bridge structures is an important topic due to the increasing need to get accurate information in a visual way. Registration between as-built laser data and global design reference one is necessary to guarantee the validity and dependency of the proposed model. This research presents a new registration method based on artificial neural networks (ANN) methodology. A developed software is implemented to apply ANN and to achieve the research objective. A steel structure bridge is chosen for the application of the proposed system. A point cloud laser data (as built) of the bridge is registered to the design model. The results show that the developed registration method is potential and reliable due to the insignificance of the error between both as-built model and the design model. The assumed level of significance is 95% and the error between as-built model and the design model after the registration process is found to be less than 5%. So, one concludes that the developed method can be used as a registration method for the laser scanning bridge structures. Some recommendations are presented to the future study concerned with using deep learning (DL) to apply the registration process to get better results.

Quasars are nowadays the basis to determine the world’s absolute orientation in space by radio interferometry (VLBI). The global network of baselines measured by the used radio telescopes, which vary greatly in size, is subject to various influences that have an impact on the International Terrestrial Reference Frame. Among others, those influences are imperfections of individual panels of the dishes, a possible elevation dependent deformation of the whole dish and a shift of the reference point due to gravitational influences. In this study, we monitor the elevation dependent deformation of the main reflector of the 20 m radio telescope of the Geodetic Observatory Wettzell by a Leica RTC360 laser scanner. For this task, we mount the terrestrial laser scanner overhead near the subreflector to capture the surface of the moving dish at each elevation angle. This study focusses on 1) introducing further redundancy in the measurement and processing strategy to gain a reliable and accurate result even the used scanner is a no high-end one. This furthermore leads to 2) investigations whether there are differences in the results between in related work used high-end scanners and the RTC360 and thus 3) whether the RTC360 proves to be capable to detect deformations at a radio telescope’s main reflector. Using these three foci, we show that deformations in the main reflector between elevations can be reliably determined areal and in focal length by redundant measurements with the RTC360. It is also shown that the results are less sensitive to axis errors compared to those obtained with high-end scanners. However, the compensations also show that the application scanner has certain systematics, which must be investigated in further steps.

Advances in digitization technologies have made possible the digitization of entire archaeological sites through a combination of technologies, including aerial photogrammetry, terrestrial photogrammetry, and terrestrial laser scanning. At the same time, the evolution of computer algorithms for data processing and the increased processing power made possible the combination of data from multiple scans to create a synthetic representation of large-scale sites. Finally, post-processing techniques and the evolution of computer and mobile GPUs and game engines have made possible the exploitation of digitization outcomes to further scientific study and historical preservation. This route was opened by the gaming industry. In terms of research, the exploitation of these new assets in conjunction with new visual rendering technologies, such as virtual and augmented reality, can create new dimensions for education and leisure. In this paper, we explore the usage of large-scale digitization of a heritage site to create a unique virtual visiting experience that can be accessed offline in VR and AR and on-site when visiting the archaeological site.

The urban climate is receiving increased attention mainly due to climate change. There are several ways to mitigate the urban climate, but green spaces have an advantage over other cooling systems because, in addition to their climate function, they provide several other ecosystem services that enhance the sustainability of urban systems. The cooling effect of green spaces varies depending on their species composition, the structure of the vegetation, the size and shape of the green spaces or the specific characteristics of the plants. Therefore, the exact quantification of urban green space’s cooling effect is of critical importance in order to be effectively applied in urban planning as a measure of climate change adaptation. In this paper, we quantified the difference in the cooling effect between urban green spaces depending on their vegetation structure (grass versus trees) and their size, and assessed to what distance from the urban green space its cooling effect can be observed. Urban green spaces were identified using Landsat orthophotomosaic and airborne laser scanning. The urban temperature was calculated as the land surface temperature (LST) from Landsat data using a single-channel method. To quantify differences in the magnitude of the cooling effect of green spaces and the distance from the edge of the green space over which the cooling effect occurs, we used a one-way analysis of variance and regression analyses. Our results show that the cooling intensity, as well as the cooling distance, are dependent on the size and structure of the green space. The most significant cooling effect is provided by large green tree spaces, where the cooling intensity (difference of LST compared to an urban area without vegetation) was almost 4.5 °C on average (maximum almost 6 °C) and the cooling distance was significant up to 90 m (less significantly up to 180 m). Large grass spaces and medium tree spaces have similar effects, with a higher cooling intensity (2.9 °C versus 2.5 °C on average) however, the cooling effect extends to a greater distance (up to 90 m) for medium tree spaces compared to large grass spaces, where the cooling effect only extends to 30–60 m. Small areas with trees and medium and small grass areas without trees have an average cooling intensity below 2 °C.

Reservoir development in the petroleum industry starts with the drill bit. A drill bit’s dull condition must be closely monitored since it significantly influences the efficiency and the cost of drilling operations. The dull condition check procedure is called drill bit grading and is essentially a change detection problem to determine the state of the drill bit, in particular the wear of the cutting teeth inserts. Currently, the grading is conducted manually on-site, which is error-prone and highly subjective. Laser scanning technology offers a potential solution to overcome the shortcomings of existing practice. The integration of LiDAR (Light Detection and Ranging) on the newly-launched iDevices, the iPhone 12 Pro and the iPad Pro 2020 offers new opportunities for close-range measurement given their huge customer base and low cost. The goal of this research is to investigate the performance of these devices, and to develop a tool for the drill bit grading. Since bit grading is significantly impacted by the performance of the sensor, several basic tests were first conducted under controlled experimental conditions, e.g., the room temperature and ambient lighting and measurement surface. The temporal stability of the iDevices was examined by capturing a series of datasets of a flat wall over forty-five (45) minutes, then the effect of range, reflectivity and incidence angle on data quality was tested by measuring the Spectralon targets at different situations. The performance tests found that using only the LiDAR data was not sufficient for drill bit grading. Thus, a preliminary grading system based on the fusion of LiDAR and color camera is proposed by modelling the post-drilling bit and detecting the changes.

Employing terrestrial laser scanners (TLS) for geodetic deformation measurements requires attaining the highest possible accuracy. In this paper, we estimate the influence of varying incidence angles (IA) and materials on measurements regarding the distance component. Considering not only stochastic characteristics, the use of a scanning total station enables additionally the study of systematic distance deviations. By using the total station ocular, the device is brought into the local coordinate system of a laser tracker via position resection and intersection. The point cloud recording, with a Close-Range scanner, represents the reference. Due to transformation into a common coordinate system, defined by a laser tracker, a distance driven point comparison is possible. To test a large number of conditions an automated setup was developed. For each device, a suitable interface was implemented in the Robot Operating System. After the specimen has been set up, an automatic measurement can be performed for data acquisition. We can demonstrate that different building materials and varying IAs cause systematic distance deviations up to 3 mm magnitude. For measurement objects, this kind of correction must be considered, especially when the measurement configuration varies between measurement epochs. It can be demonstrated that the values and characteristics observed in the laboratory agree to those obtained on-site. However, the chosen approach thereby reveals previously unrecognized challenges that need to be considered for the use of TLS in high-accuracy deformation analysis.

This contribution presents a B-spline-based approach of area-wise deformation analysis applied on elements of a double curved wooden tower. The monitored object is the Urbach Tower with a height of 14 m. Terrestrial laser scans from two epochs acquired under real-world conditions are used for approximating two jointly parametrized B-spline surfaces of the tower’s outer shell. The stochastic model of the observations used within the surface approximation is based on elementary error theory and is defined by a synthetic variance-covariance matrix (SVCM). In addition to previous work on this topic, the object’s dimension is extended from a few dm to a few m and the measurement distance ranges from 20 to 60 m. Moreover, environment specific error sources are addressed in the SVCM, revealing the effect of the object’s dimension as well as of additional elementary errors on the estimated B-spline surfaces and the subsequent deformation analysis. Based on constructed points pairs using a grid of surface parameters, rigid body movements of the object under investigation are estimated while at the same time distorted regions of the wooden tower are detected. All results of the deformation analysis are statistically verified using hypothesis tests based on the elementary error model propagated through the processing algorithms of surface estimation and deformation analysis. The results demonstrate that during the modelling and deformation analysis, the measurement noise is reduced and therefore distorted regions are detectable in a statistically correct way.

Laser scanners with rotational Risley prisms produce scan patterns that can be classified as a type of rhodonea curve, because of their symmetry. The present study builds upon the novel, graphical method that we have developed to simulate and analyze such patterns using a commercially available mechanical design program, CATIA V5R20 (Dassault Systems, Paris, France). This graphical method has both the advantage of simplicity (regarding analytical methods) and of generating exact scan patterns (in contrast to approximate methods). The aim of this work is to utilize this method to study symmetry properties of scan patterns produced by a pair of rotational Risley prisms. A multi-parameter analysis is performed, considering the characteristic parameters of the approached scanner: refractive indexes and angles of the prisms, as well as their rotational velocities. Furthermore, Marshall’s parameters are considered: ratios of the rotational velocities and of the prism angles. Because the symmetries are identical for scan patterns generated by all the four possible configurations of a pair of prisms (and only their dimensions are different), the shape of these patterns is studied only for one of these configurations. Therefore, without losing generality, the symmetries of the patterns produced by such scanners are determined, as well as some of their characteristic dimensions. Rules-of-thumb were obtained to be able to generate patterns that are appropriate for a specific application. Moreover, we demonstrated that the existing symmetries simplify the process of obtaining the scan patterns by identifying repetitive parts (defined as structures of symmetry) of a pattern.

Modern digitization technologies have created an increasing number of possibilities for capturing the physical dimensions and appearance of archaeological artifacts and sites in 3D. The usage of such data is usually targeted to the research, study, and documentation of our cultural heritage. At the same time, the increasing quality of the produced digitizations has opened new possibilities for the further exploitation of digitization outcomes in a wider context than initially expected. A pioneer in this direction was the gaming industry, where photogrammetry has been recently employed to achieve extreme photorealism. Of course, challenges still exist, especially when digitization accuracy is of importance, such as in the case of large-scale archaeological sites. Further challenges regard the need to combine indoor and outdoor scenes that pose requirements in the selection of the appropriate digitization modalities and post-processing strategies. In more detail, the challenges relate to the appropriate usage of existing technologies, organization issues in terms of digitization visits, the combination and registration of data, data acquisition, and data processing methodologies, etc. In this paper, we demonstrated a methodology for the digitization of archaeological sites that can be used for creating digital assets suitable for various scenarios including research, education, and entertainment.

Nowadays, many construction projects in KSA still struggle with cost overruns and delay in activities. Therefore, automatic monitoring approaches are needed in the construction progress monitoring domain (CPM) to address these concerns. Thus, this paper proposed a system integrating a BIM-planned model with site laser scans, as laser scanners showed massive potential in the CPM domain. The algorithms of the proposed system recognized 3D objects based on the intersection between models, alignment accuracy, and Lalonde features. The proposed system combined 3D object recognition technology with 5D information data into a 5D progress tracking system using earned value (EV) principles. The reason behind that is a lack of research regarding conducting a 5D assessment integrated BIM with 3D sensing technology in the CPM domain. The proposed system was verified using field data from a superstructure construction project where the object recognition indicators showed a 98% recall and 99% precision in recognizing 3D objects. The proposed system also used a color-coding system to address the condition of each element based on its recognition and scheduling state and address any occlusions while calculating the recognized objects. The results also revealed an automatically updated status of the project’s progress in terms of schedule(4D) and cost(5D). The automated results were also validated with a manual calculation, where a slight variation (1.35%) was observed between those calculations. This system demonstrates a degree of accurate progress tracking, automatically exceeding manual performance with less computational time.