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Freeform surfaces like tensor product B-spline surfaces have been proven to be a suitable tool to model laser scanner point clouds, especially those representing artificial objects. However, when it comes to the modelling of point clouds representing natural surfaces with a lot of local structures, tensor product B-spline surfaces reach their limits. Refinement strategies are usually used as an alternative, but their functional description is no longer nearly as compact as that of classical tensor product B-spline surfaces, making subsequent analysis steps considerably more cumbersome. In this publication, the approximation quality of classical tensor product B-spline surfaces is improved by means of local parameterization. By using base surfaces with a local character, relevant information about local structures of the surface to be estimated are stored in the surface parameters during the parameterization step. As a consequence, the resulting tensor product B-spline surface is able to represent these structures even with only a small number of control points. The developed locally parameterized B-spline surfaces are used to model four data sets with different characteristics. The results reveal a clear improvement compared to the classical tensor product B-spline surfaces in terms of correctness, goodness-of-fit and stability. [ABSTRACT FROM AUTHOR]

The process of engineering construction typically impacts the nearby existing buildings, causing either localized or widespread deformation of these structures. The application of deformation monitoring technology enables the timely identification of damage or uneven deformation, thereby facilitating the implementation of appropriate maintenance and repair actions. This paper explores the application of ground-based synthetic aperture radar (GB-SAR) in building facade deformation monitoring. GB-SAR acquires two-dimensional (2D) images and measures deformation along the line of sight (LOS) direction through interference calculation. In order to accurately determine the location of deformation and retrieve the elevation information of image pixels, it is usually required to utilize external three-dimensional (3D) data to reconstruct the 3D coordinate of these pixels, which is known as geocoding, or georeferencing. In the case of the GB-SAR system, it is necessary for the observer to measure the angles between the antenna orientation, the radar movement direction and the reference plane of the local surveying coordinate system. Nevertheless, the measurement of these attitude angles may be overlooked in practice, and the impact of small attitude angles or their measurement errors on GB-SAR geocoding may be disregarded, which directly affects the slant range projection (SRP) calculation of the external 3D data, thereby leading to biased 3D coordinate reconstruction of GB-SAR pixels. This paper proposes a method to calculate the SRP coordinates of point cloud data considering the attitude inclination angles of radar sensor, and perform matching calculations on the high-quality pixels (HQPs) with the point cloud after SRP to extract building facade deformation. The results demonstrate that the method is capable of effectively mitigating the influence of the radar attitude inclination angles, resulting in a reduction of the average deviation of 3D coordinates to approximately one-third of the value without consideration of the sensor’s attitude in a real-world building monitoring experiment. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology with which to measure the slight erosion undergone by valuable heritage pieces in a short period of time. The problems dealt with by our method concern the irregular (free-shape) geometry of the piece to be measured, the difficulty involved in achieving the fine registration required among different samples of the piece, the slight loss of material in a short period of time and the suitable definition of descriptors that will help to carry out a reliable qualitative and quantitative analysis. This document proposes a basic methodology that is able to tackle each of the aforementioned problems. An in-depth explanation of the degradation analysis has been carried out on a representative case study, including the qualitative and quantitative procedures employed. The results obtained lead us to believe that this methodology could be reproduced and applied to similar degradation problems related to old buildings. [ABSTRACT FROM AUTHOR]

Trace detection in tunnel faces is critical for preventing failures such as spalling in tunnel excavations. This paper proposes a novel method, referred to as the Roughness-CANUPO (R–C) Method, for the automatic detection of these traces in 3D point clouds obtained from tunnel faces, in which its combines roughness analysis with the CANUPO machine learning algorithm to improve the accuracy and efficiency of trace detection. In this study, images were collected from six sites and point cloud data of 6 sites were obtained by 3D reconstruction. Points representing rock masses in the collected 3D point cloud data can be filtered by roughness analysis in the R–C methods. Roughness analysis can not only significantly reduce the analysis time of CANUPO machine learning, but also increase the accuracy of CANUPO analysis. In this paper, the local neighbourhood radius (LNR) and filtering ratio optimized in the roughness analysis and the roughness for filtering discontinuities were evaluated. The filtered point cloud data automatically extract only the trace point cloud by the CANUPO classifier. The extracted trace was projected onto the original data to accurately designate the location of the trace. Conducting the R–C method yields a significant result regarding discontinuity traces classification by reaching the level of accuracy ranging from 95.9% to 98.9%. [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]

In this paper we propose a monitoring method that allows the inclusion of point clouds into a geodetic monitoring network. Consequently, network adjustment and a rigorous deformation analysis can be performed allowing consistent error propagation and trustful significance calculation. We introduce a supervised pipeline based on ICP-matching of small-scale laser scan patches. It is specially designed for geo-monitoring applications and allows to improve the spatial resolution as well as the network geometry of monitoring networks in inaccessible hazardous areas in the mountains, where the installation of a sufficient number of targets is difficult. We apply our method to two datasets. The first is a monitoring setup in the laboratory, where we establish the parameters for the supervised patch selection and demonstrate how the network geometry is improved. Second is the real case study of Mt. Hochvogel, where the proposed method helps to clearly improve the spatial resolution of deformation vectors. [ABSTRACT FROM AUTHOR]

In recent years, the application of real scene 3D technology has become widespread in urban planning and cultural heritage protection. However, there has been relatively little attention paid to the construction of real scene 3D models for special natural landscapes such as caves. Given the global distribution of karst topography and the large number of naturally developed caves with diverse types, unique landscape styles, and significant scientific value, this paper enriches the research in this field. By combining ground-based and aerial remote sensing techniques, and based on 3D laser scanning and photogrammetry, we have successfully constructed a real scene 3D model of the internal structure of a karst cave with a precision better than 4 cm. Utilizing Unmanned Aerial Vehicle (UAV) oblique photography, we established a real scene 3D model of the external karst landform with a precision better than 2 cm. We also integrated the internal and external 3D models of the cave, developing a new, complete, and high-precision method for constructing real scene 3D models of karst cave landscapes. Furthermore, we proposed a method for texture reproduction in the dark environment inside the caves, enhancing the reproduction and visual appeal of the real interior. The establishment of high-precision real scene 3D models can not only serve as an effective tool for scientific research on caves but also, as replicas of the real world, play a crucial role in public dissemination and education, thereby enhancing public understanding of cave geological landscapes. [ABSTRACT FROM AUTHOR]

For more than a dozen or so years now, there has been growing interest in the use of modern laser scanning measurement methods in numerous mining operations engaged in underground excavation. However, the simple possession of a scanner does not guarantee satisfactory measurement results. This study sets out the results of scanning mine excavations in an active mine and describes the current guidelines on various aspects of the measurement process. These guidelines were developed on the basis of several hundred measurements carried out over the last dozen or so years. This study also outlines the typical measurements errors observed over the course of many years. These errors, resulting partly from hardware limitations and partly from human error when planning or actually performing measurements, were an important factor behind the introduction of standards regulating underground measurements. This study discusses in detail not only scanning that utilises traditional stationary laser scanners but also scanning based on mobile scanners. It also presents possible areas of future technological development in line with global trends. [ABSTRACT FROM AUTHOR]

Copyright of Science & Technology of Cereals, Oils & Foods is the property of Science & Technology of Cereals, Oils & Foods Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

In this paper, we discuss the requirements and technical challenges within the EHEM project, Enhancement of Heritage Experiences: The Middle Ages, an ongoing research program for the acquisition, analysis, documentation, interpretation, digital restoration, and communication of medieval artistic heritage. The project involves multidisciplinary teams comprising art historians and visual computing experts. Despite the vast literature on digital 3D models in support of Cultural Heritage, the field is so rich and diverse that specific projects often imply distinct, unique requirements which often challenge the computational technologies and suggest new research opportunities. As good representatives of such diversity, we describe the three monuments that serve as test cases for the project, all of them with a rich history of architecture and paintings. We discuss the art historians' view of how digital models can support their research, the expertise and technological solutions adopted so far, as well as the technical challenges in multiple areas spanning geometry and appearance acquisition, color analysis and digital restitution, as well as the representation of the profound transformations due to the alterations suffered over the centuries. [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]

Close-range sensing has yet to attain the status of being a dependable source for in situ forest information as the conventional field inventory. Each solution has its advantages and disadvantages in terms of accuracy, completeness, and efficiency. For a forest area, Terrestrial Laser Scanning (TLS) has the highest data quality, but is limited to static perspectives and lack the efficiency. Mobile Mapping Systems (MMS) systems gain on the efficiency but compromise the data quality. More recently, under-canopy UAV caught attentions for its potential to leverage the advantages of both TLS and MMS systems. This study demonstrates the feasibility of autonomous forest in situ investigation using an autonomous under-canopy UAV Laser Scanning (ULS) system, and evaluates the performance of such system in deriving key forest and tree attributes through a comparison with other close-range sensing systems such as the TLS and the Personal Laser Scanning (PLS). The under-canopy ULS system uses an onboard LiDAR sensor to aid its self-traverse in an unknown forest environment and to collect point cloud data during its movement inside the forest. Key factors influencing the systems' overall performance were investigated via various experiments. The point cloud data collected by the under canopy autonomous ULS system deliver similar stem capturing capacity as TLS in single layer forest stands with less undergrowth. The RMSEs of the DBH estimates were 0.81 cm (3.80%), 4.12cm (19.92%), and 5.13cm (22.01%), respectively. The RMSEs of the stem curve estimates were 1.27 cm (5.48%), 3.97 cm (17.63%), and 5.18 cm (22.49%), respectively. The geometric accuracy and the completeness of the point cloud significantly improved when the trajectory was densified. More studies on autonomous route planning in complex unknown forest is required to improve the system mobility, data quality, and the applicability of such systems in future practical forest in situ observations. [ABSTRACT FROM AUTHOR]

Key message: Analyzing fine branch length characteristics in beech trees using single-tree QSMs derived from laser scanning reveals insights into drought-induced changes in vitality, which include branch shedding and reduced shoot growth. Climate change causes increasing temperatures and precipitation anomalies, which result in deteriorations of tree health and declines in ecosystem services of forests. It is therefore crucial to monitor tree vitality to preserve forests and their functions. However, methods describing tree vitality in situ are lacking reproducibility or are too laborious. Thus, we tested a laser-scanning based approach, assuming that an objective measurement of a tree's outer shape should reveal changes according to tree vitality. QSMs of similarly sized beech trees from stands with varying degrees of drought damage were used. Absolute and relative fine branch lengths, their ratio to lower order branches' lengths and their progressions over relative height were targeted to identify fine branch dieback and reduced growth. The absolute fine branch length was significantly lower for less vital beech trees, especially within the upper crown, leading to a less top-heavy vertical distribution of fine branches and a reduced fine-to-base order branch length ratio. Hence, height-dependent characteristics of fine branch lengths differed between vitalities. We conclude that using fine branch length characteristics derived from QSMs can be helpful in vitality assessments of beech trees. Still, uncertainties with regard to the plotwise assessment and problems with QSM quality are present. [ABSTRACT FROM AUTHOR]

Grain surface movement monitoring is an important part of the daily inventory inspection of national grain reserves, and is a new requirement for grain storage supervision. In order to solve the technical problems of the traditional grain surface movement monitoring, this paper proposed a laser radar-based grain surface movement monitoring method. A full-size experimental platform that can simulate the real grain pile state was established, and a high-precision laser three-dimensional measurement device was utilized to design an algorithm to identify the abnormal movement of the grain surface of the bulk grain pile based on the laser scanning point cloud data and the information of entering and exiting the warehouse operation. The algorithm was examined and verified through the experimental platform. The results showed that: the method can directly obtain high-precision coordinate information of the grain pile surface, which overcome the problem of insufficient data accuracy of image recognition technology. The constructed algorithm of grain surface motion discrimination based on the coordinate information of the grain pile shape and the data of entry and exit operation status was capable of realizing reliable quantitative computatio. The proposed method was applied to the actual grain warehouse scenario, which verified the feasibility and validity of the method, and it was able to satisfy the dynamic grain inventory supervision needs. The proposed method was applied to the actual grain silo scenario to verify the feasibility and effectiveness of the method, which can meet the demand of grain stock dynamics supervision and provide a new technology for online monitoring and early warning of grain surface variation.

Abstract In recent years, the application of real scene 3D technology has become widespread in urban planning and cultural heritage protection. However, there has been relatively little attention paid to the construction of real scene 3D models for special natural landscapes such as caves. Given the global distribution of karst topography and the large number of naturally developed caves with diverse types, unique landscape styles, and significant scientific value, this paper enriches the research in this field. By combining ground-based and aerial remote sensing techniques, and based on 3D laser scanning and photogrammetry, we have successfully constructed a real scene 3D model of the internal structure of a karst cave with a precision better than 4 cm. Utilizing Unmanned Aerial Vehicle (UAV) oblique photography, we established a real scene 3D model of the external karst landform with a precision better than 2 cm. We also integrated the internal and external 3D models of the cave, developing a new, complete, and high-precision method for constructing real scene 3D models of karst cave landscapes. Furthermore, we proposed a method for texture reproduction in the dark environment inside the caves, enhancing the reproduction and visual appeal of the real interior. The establishment of high-precision real scene 3D models can not only serve as an effective tool for scientific research on caves but also, as replicas of the real world, play a crucial role in public dissemination and education, thereby enhancing public understanding of cave geological landscapes.

Here, we propose a method for the semantic segmentation of 3D point clouds based on functional data analysis. For each point of a training set, a number of handcrafted features representing the local geometry around it are calculated at different scales, that is, varying the spatial extension of the local analysis. Calculating the scales at small intervals allows each feature to be accurately approximated using a smooth function and, for the problem of semantic segmentation, to be tackled using functional data analysis. We also present a step-wise method to select the optimal features to include in the model based on the calculation of the distance correlation between each feature and the response variable. The algorithm showed promising results when applied to simulated data. When applied to the semantic segmentation of a point cloud of a forested plot, the results proved better than when using a standard multiscale semantic segmentation method. The comparison with two popular deep learning models showed that our proposal requires smaller training samples sizes and that it can compete with these methods in terms of prediction. [ABSTRACT FROM AUTHOR]

Installation quality check is essential for ensuring the construction quality of prefabrication construction. The existing techniques for assessing the installation quality of prefabricated wall panels heavily depend on manual inspection and contact-type measurements, which is labor intensive and slow. Laser scanning was previously adopted in construction quality check, however, few studies have focused on using laser scanners to assess the verticality of prefabricated wall panels, and no method has been developed for effective practical implementation. This study proposes a streamlined laser scanning approach for onsite verticality check of prefabricated wall panels. Based on systematic experiments of using the point cloud data collected by different types of laser scanners, and 25 prefabrication wall panels of four shapes, this study validates the proposed method and compares the use of different laser scanners. To facilitate an effective streamlined process for practical use, this study identifies the point cloud segmentation parameters under different laser scanning data sets and suggests suitable parameters for these case scenarios. These parameters can be adopted directly or used as references for practical application of the proposed laser scanning method in the installation verticality check. This study contributes to improving the efficiency of installation quality check of prefabrication construction, and facilitating the digital evolution of the construction industry. Practical Applications: Checking the verticality of the installed prefabricated wall panels is crucial in construction quality control. However, traditional methods for assessing the installation quality of prefabricated wall panels heavily depend on manual inspection and contact-type measurements, which is labor-intensive, slow, and costly. For project involves a large number of same or similar type of prefabricated construction elements, this repetitive work also causes human fatigue and in-efficiency. This paper proposes a laser scanning method to streamline the quality check process for the installation of prefabricated wall panels. By systematically experimenting with the point cloud data collected by different types of laser scanners for various wall panels of different shapes, this study validates the effectiveness of the proposed method. Another major contribution of this research is preidentification of optimal segmentation parameters for laser scanning point cloud. This means construction professionals can use these parameters directly or as references for identifying suitable segmentation parameters for other projects. The streamlined laser scanning method contributes greatly to improving the efficiency of installation quality check of prefabrication construction practice, especially when large number of identical or similar elements are used. [ABSTRACT FROM AUTHOR]

Close-range sensing has yet to attain the status of being a dependable source for in situ forest information as the conventional field inventory. Each solution has its advantages and disadvantages in terms of accuracy, completeness, and efficiency. For a forest area, Terrestrial Laser Scanning (TLS) has the highest data quality, but is limited to static perspectives and lack the efficiency. Mobile Mapping Systems (MMS) systems gain on the efficiency but compromise the data quality. More recently, under-canopy UAV caught attentions for its potential to leverage the advantages of both TLS and MMS systems. This study demonstrates the feasibility of autonomous forest in situ investigation using an autonomous under-canopy UAV Laser Scanning (ULS) system, and evaluates the performance of such system in deriving key forest and tree attributes through a comparison with other close-range sensing systems such as the TLS and the Personal Laser Scanning (PLS). The under-canopy ULS system uses an onboard LiDAR sensor to aid its self-traverse in an unknown forest environment and to collect point cloud data during its movement inside the forest. Key factors influencing the systems’ overall performance were investigated via various experiments. The point cloud data collected by the under canopy autonomous ULS system deliver similar stem capturing capacity as TLS in single layer forest stands with less undergrowth. The RMSEs of the DBH estimates were 0.81 cm (3.80%), 4.12cm (19.92%), and 5.13cm (22.01%), respectively. The RMSEs of the stem curve estimates were 1.27 cm (5.48%), 3.97 cm (17.63%), and 5.18 cm (22.49%), respectively. The geometric accuracy and the completeness of the point cloud significantly improved when the trajectory was densified. More studies on autonomous route planning in complex unknown forest is required to improve the system mobility, data quality, and the applicability of such systems in future practical forest in situ observations.

In 2020, Apple incorporated a LiDAR sensor system into its smart devices, being the first to offer the laser scanning technology to the general consumer. This article investigates how a low-cost LiDAR scanning system integrated into Apple devices performs in comparison to professional geodetic terrestrial laser scanners. In addition to providing a brief overview of the functionality of the measurement system within Apple devices, a comprehensive literature review was conducted. Various authors have examined the system either in comparison to other spatial data capture methods or in studies of its applicability across different fields. In this article, we examined the geometric quality of the lidar scanning system embedded in the Apple iPad Pro device for the purpose of 3D modeling of indoor building spaces. We conducted experiments in a smaller (~1 m) and larger (~10 m) test field and evaluated the geometric quality of the captured data. The findings indicate that the Apple system cannot achieve relative positional accuracy better than 10 cm and is primarily suitable for creating informative 3D representations.

Abstract. This article provides an overview of modern remote sensing techniques in archaeology and their practical applications. The widespread use of GIS technologies and remote sensing methods such as photogrammetry and laser scanning is a distinguishing characteristic of contemporary archaeology. Remote sensing data is employed not only for the analysis of 3D archaeological objects and territories but also in the digital terrain models (DTMs) analysis to search for and identify potential archaeological excavation sites. The introduction of remote sensing methods in archaeology has brought about a change in the approach to conducting archaeological studies. In the field of international research, a distinct stage known as predictive archaeology, which involves preliminary reconnaissance of an area before excavation, has emerged. The study is focused on the archaeological sites of Stantsiya Krasavka and Akhmatskoe Gorodishche, located in the Atkarsky and Krasnoarmeysky municipal districts of the Saratov region. The selected study areas applied the DTM analysis, specifically using the “Hillshade” technique (analytical shading relief), which allows for the detection of previously overlooked terrain features. Based on the results, the potential of this technology for identifying individual archaeological objects using contemporary open DTMs and field geodetic survey data was analyzed. Experimental determination of the optimal DTM resolution for the identification and analysis of objects was conducted in areas previously subject to archaeological research. The experiments and comparative analysis of various laser scanning technologies led to the identification of optimal methods and filtering parameters to “exclude” vegetation and generate DTMs.

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]

Introduction: The research is aimed to identify the vulnerable areas of quarry slopes through the creation of a stress-strain state model for the rock mass at the Vostochny quarry, East Saryoba field of the Zhi-landy Group of cupriferous sandstones, as well as their subsequent strengthening. Methods: The research is based on the development of a database containing information on mining-geological, geophysical, geodetic and aerospace surveys. The authors of the research use modern geodetic, aerospace and geophysical technologies for scientifically based predicting of technogenic disasters and the rock mass stress-strain state modeling to ensure safe and optimal mining of fields in difficult mining-geological conditions. Results: The results obtained show that the strengthening of weakened quarry slopes based on the rock mass stress-strain state modeling contributes to the scientific-practical profitability of field mining and provides safe mining in difficult mining-geological conditions. Discussion: Novelty is in the scientific substantiation of the method for strengthening quarry slopes, which is based on the rock mass stress-strain state modeling. The research is of great practical importance, as the rock mass stressstrain state modeling increases the reliability of predicting the rock mass state during its mining. Strengthening of quarry slopes using the proposed method reduces risks and increases safety and economic efficiency of mining the solid mineral deposits in difficult mining-geological conditions. [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 urban three-dimensional (3-D) model, which can truly and vividly express the 3-D spatial information of ground objects, was an essential link in the process of smart city construction. The backpack 3-D laser scanning systems had gradually become an important technical means to build urban 3-D models because of their high efficiency and high fineness. In this paper, the error source of backpack point cloud data was analysed based on the composition of backpack 3-D laser scanning system. The distribution of point cloud error was statistically analysed by designing experiments. It was found that there was a systematic error in the backpack 3-D laser scanning point cloud. There were many factors influencing the system errors and they were superimposed on each other. In order to solve this problem, an error compensation model with additional system parameters based on a multiple linear regression algorithm was constructed. The results showed that this model can weaken the influence of system errors on the backpack point cloud, effectively improve the accuracy of the backpack point cloud, and provide reliable point cloud data for subsequent processing of the building point cloud. [ABSTRACT FROM AUTHOR]

Copyright of Virtual Archaeology Review is the property of Virtual Archaeology Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In art design, 3D printing technology is crucial, and more and more creators conceive scenes using 3D modeling software to get a three-dimensional and beautiful work. Due to the large amount of noise and redundant points in the raw data collected during the modeling process, the generation speed and rendering effect of 3D models are reduced. Given the above problems, the study designed an interactive 3D lightweight modeling system based on the combination of hand-drawn sketching and laser 3D scanning based on the streamlined algorithm. The experimental results showed that when the hand-drawn speed was 300, the number of triangular slices, model size, and time required to generate the model of the hand-drawn sketching model based on the streamlined algorithm were reduced by 67.39%, 65.48%, and 63.79%, respectively. In the real-time point cloud data streamlining process of the laser 3D scanning model, the point cloud data reduction ratio and the streamlining goodness index of the point cloud streamlining algorithm are 71.99% and 3.06%, respectively. The system performance is robust, and the data processing speed and rendering effect are good. [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]

Optical remote sensing techniques can indicate the properties of objects by observing different modalities (physical quantities) of the backscattered light at different optical wavelengths. Established examples are reflectance, fluorescence, Raman, or depolarization spectroscopy. LiDAR sensing, on the other hand, allows acquiring the geometry of objects by measuring the propagation delay of optical probing signals. Multimodal multispectral (MM) LiDAR combines these capabilities and extends conventional monochromatic LiDAR in both spectral and modal dimensions within a single instrument, thus enriching point cloud data with non-geometric information. The potentially high dimension of MM LiDAR data, however, poses significant challenges for instrumental design, data acquisition, and data processing. MM LiDAR data are structured as several or all modalities are available in each of the spectral channels. The above challenges can thus be mitigated by feature selection (FS), if the structure of the features is taken into account, i.e., if entire spectral channels or entire modalities are selected or omitted. Herein, we focus on the feature selection method for MM LiDAR and propose a multiclass group feature selection algorithm (MGSVM FS) consisting of a structural sparsity-based embedded feature selection method with an all-in-one support vector machine (SVM). It tackles jointly the challenges arising from the high dimension of the MM data and the need for a multiclass classification task while exploiting the structure of the MM data. In addition, we introduce a complete workflow for evaluating the feature selection and for decision-making. We apply the framework to selecting an optimum spectral and modal configuration for remote material classification using an experimental MM LiDAR system that provides reflectance, distance, and degree of linear polarization in 28 spectral channels of 10 nm width. For the experimental investigation, we use MM LiDAR data obtained in a controlled lab environment from thirty specimens of four material classes relevant for construction. Using all three modalities, we find a configuration with only 3 spectral channels that achieves a classification mean-F1 score of 100% within this small dataset. Similar classification performance can also be achieved with only two modalities when using more spectral channels. MGSVM FS improves the classification mean-F1 score by up to 25% as compared to random selection and outperforms two other commonly used filter and embedded feature selection methods, in this application example. The proposed group feature selection algorithm and decision-making are useful for MM LiDAR, providing a link between instrumental design, data acquisition, and data processing. However, they are also transferable to other application fields related to multiclass classification, regression, and knowledge discovery, with features structured in groups. The collected MM feature dataset, the MGSVM FS algorithm, and the evaluation pipeline are accessible online. 1 1 https://github.com/yuhan-yhyh/Dataset_Code_MGSVM-FS-MM-LiDAR.git. [ABSTRACT FROM AUTHOR]

Copyright of Turkey Lidar Journal / Türkiye Lidar Dergisi is the property of Mersin University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Turkey Lidar Journal / Türkiye Lidar Dergisi is the property of Mersin University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

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]

Terrestrial Laser Scanning (TLS) and Close-Range Photogrammetry (CRP) are advanced techniques for capturing 3D data in crime scene reconstruction, offering complementary information. Despite taking multiple scans and images from different angles to ensure a comprehensive model, limitations, such as device positioning, shadows, object distance, and laser beam angles prevent the creation of a complete crime scene model. Therefore, combining TLS and CRP data is crucial for achieving a comprehensive reconstruction. This study aims to transform a physical crime scene into a geospatial-based reconstructed model known as point clouds. The technique used was highly rich in realistic features, digitally reconstructed from TLS and CRP. The data sources were then fused via a rigid body transformation, creating a comprehensive crime scene model. The combined point cloud measurements were compared with measurements obtained from a high-precision Vernier caliper to ascertain their accuracy. The resulting Root Mean Square (RMSE) difference between the fused point cloud data and the high-precision caliper measurements was approximately ±4mm. The fusion of TLS and CRP data provides reliable and highly accurate 3D model point clouds, making it suitable for forensic applications. [ABSTRACT FROM AUTHOR]

Copyright of Fire Ecology is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Bloodstain pattern analysis (BPA) has proven to be a useful tool in forensic and criminal investigations for quite some time. Traditionally, documenting a crime scene for a bloodletting event was completed using manual techniques, physical strings, and a tape measure. In more recent years, laser scanners and 3D software programs have become a preferred method to capture accurate data that improves the validity and reliability of BPA. The initial cost of laser scanning equipment is relatively high, rendering these systems inaccessible to some police and smaller agencies. Recon-3D is a newly developed iPhone application that utilizes the iPhone LiDAR sensor in combination with video data to create 3D point clouds of crime scenes. To assess the viability of Recon-3D for area of origin analysis, two tests were performed. One was a series of bloodstain impacts which were analyzed in FARO Zone 3D software, while the second was a series of 6 repeated Recon-3D scans of two 90-degree walls which was then compared to the FARO Focus S350 scanner using CloudCompare software. A total of eight impact patterns were made at three different distances from a wall. The area of origin was measured and compared to the known location of the blood source. The average total 3D error for the area of origin set at 25, 50, and 100 cm from two perpendicular walls was found to be 6.04, 15.16, and 36.59 cm, respectively. These results are similar to past studies where programs such as HemoSpat have been used. The results of the point cloud comparison show that on average, 95% of the points from Recon-3D fall below a threshold of 3.6 mm when compared to a FARO Focus S350 laser scanner. Thus, the results of this test suggest that Recon-3D is an accurate and affordable scanning application for bloodstain patterns at crime scenes and the data provide acceptable results for area of origin analysis in BPA programs which accept laser scanner data. [ABSTRACT FROM AUTHOR]

The Roman town of Falerii Novi sits 50km north of Rome on the ancient Via Amerina. According to historical sources, it was founded after the Roman conquest of the nearby Faliscan centre of Falerii Veteres in 241 BC (Polyb. 1.65; Liv. Epit. 20; Eutrop. 2.28; Oros. 4.11; Zon. 8.18). The urban site appears to have persisted at least until the first half of the sixth century AD, with the bishopric of Aquaviva ascribed to the site in AD 465 (Duchesne, 1892). A monastery and church of Santa Maria di Falleri were founded by Cistercians and first mentioned in documents of the eleventh and twelfth centuries, now forming the only standing structure on site other than the ancient circuit walls.