Terrestrial Laser Scanning Technology Research Articles

Heritage Building Information Modelling (HBIM): A Review of Published Case Studies

Abstract. This paper presents a systematic review of published case studies on Heritage Building Information Modelling (HBIM) since 2018, and identifies research gaps in the subject matter. Building upon the foundational work of Ewart and Zuecco (2019), this research aims to reveal the latest trends in HBIM implementation, identify recent developments of HBIM technologies, changes in the purpose of HBIM programs and stakeholder roles and responsibilities, and uncover knowledge gaps that provide avenues for future research. Utilizing the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) approach, two major academic databases, Scopus and Web of Science (WOS), were searched, resulting in a rich and diverse dataset for analysis. The paper reports findings on the status of reality capture techniques used to acquire data for HBIM development, focusing on terrestrial laser scanning (TLS) technology. The review highlights the benefits and limitations of TLS for data acquisition in HBIM, as well as the integration of TLS with other reality capture technologies, such as Structure from Motion (SfM) and photogrammetry. The paper further outlines the typical workflow for processing TLS scan data and explores the integration of multiple point clouds for comprehensive heritage site modeling. In addition to the state of the art, this systematic review also uncovers several research gaps in the field of HBIM that offer opportunities for future research and innovation, including the lack of guidelines for data acquisition in HBIM programs, the predominantly manual development process of HBIM from TLS point cloud data, and the under-utilized capacity of TLS for long-term monitoring and change detection. This comprehensive review provides valuable insights into the current landscape of HBIM, offering guidance for future research and development in the heritage sector and highlighting areas in need of further investigation to advance the field.

A Study on Three-Dimensional Modelling of the Baitul Ilmi Mosque's Itera Using Terrestrial Laser Scanner Technology

As advancements in three-dimensional (3D) modeling continue to progress, the demand for precise and efficient measurement techniques has led to significant innovations in the methods and tools used for creating 3D models. Among these, the utilization of Terrestrial Laser Scanners (TLS) has become increasingly popular. This study focuses on the integration of TLS and total station technologies for 3D modeling of a mosque. The total station was employed to conduct five sets of perfectly bonded closed polygon measurements, each consisting of five polygon points, from which three marker points were derived. Concurrently, the TLS was used to perform a comprehensive scan of the mosque from 17 different positions. The data obtained from the TLS scan provided a detailed 3D model, while the total station measurements served as control points to ensure the model's global coordinate accuracy. The processing of the closed polygon data was executed using the Bowditch method, and the TLS data was registered using the cloud-to-cloud method. This approach yielded an overall quality assessment, including a bundle error of 0.008 m, an overlap of 27%, a strength of 65%, and a cloud-to-cloud discrepancy of 0.008 m. The integration of point clouds with total station coordinates resulted in an error margin of 0.160 m. Geometric validation of the model was conducted by comparing its dimensions to measurements obtained using a measuring tape, which yielded a Root Mean Square Error (RMSE) of 0.045 m.

Tree parameter extraction method based on new remote sensing technology and terrestrial laser scanning technology

Ground LiDAR is a terrestrial LiDAR system that is often used for terrain and geomorphic mapping. Ground-based LiDAR can be used to collect more local and short-range data, making it ideal for mapping smaller areas with high precision. In order to solve the rapid extraction of tree parameters in the national public welfare forest survey, the ground-based LIDAR was used to obtain the point cloud of trees, and the point cloud data was registered, denoised, normalized, sliced, parameter extracted, etc., and the parameters of individual trees in the forest were obtained. The Bland-Altman consistency test is used to test whether the method of extracting tree parameters from point clouds is consistent with the traditional measurement method. The experimental results show that the point cloud data obtained by the ground-based LIDAR can quickly, conveniently and accurately extract the tree parameters, which is consistent with the traditional tree parameter extraction method, and has the advantages than the traditional tree parameter measurement, such as point cloud, image and traceability. It has a unique advantage in establishing a tree database. It is suggested that LIDAR should be used for forest survey in the future.

A Broadly Applicable Coarse Alignment Framework for the Point Cloud of Hull Blocks

_ The terrestrial laser scanning (TLS) technology, which has been widely used in recent years, provides a new approach to control the construction quality of hull blocks in shipyards. As the cloud-model registration problem plays the most significant role in the data processing stage of utilizing the TLS devices, this paper concentrates on developing a broadly applicable coarse alignment framework for the point cloud of hull blocks. This framework involves two steps: the recognition of the connection regions of the point clouds and the coarse registration method according to the classification results. To detect the connection regions automatically, a hand-crafted simple model of the connection regions of hull blocks is built and its supporting detection method is proposed, besides, considering the recent overwhelming success of deep learning methods, a deep learning network suitable for large hull block datasets is constructed according to the Point-Net, and convolutional neural networks paradigms. Then, the coarse alignment method based on the detected connection regions is proposed. Experimental results illustrate the good performance of the proposed framework. Keywords computers in construction; shipbuilding; automation

ACCURACY RESEARCH OF THE EFFECT OF LOCAL SURFACE MODELING METHODS ON THE GENERATION OF 3D MODELS OF HISTORICAL OBJECTS WITH ROCK-BASED BUILDING STRUCTURES USING OPEN-SOURCE SOFTWARE

Abstract. The paper describes the effect of the local surface modelling methods known as plane, quadric and triangulation on the generation of the 3D mesh models of the historical objects with rock-based building structures using Cloudcompare, an open-source software for point cloud data processing. The methodology begins with data collection of the 3D test objects using terrestrial laser scanning technology, the pre-processing of the point cloud data, the point cloud subsampling process, the process of generating of the local surface modelling data, the process of generating the 3D mesh models and finally, the analysis, which involves the 3D surface deviation analysis between the generated 3D mesh models. The overall results shows that there are no significant differences between the 3D mesh models that was generated from all the three local surface modelling methods. The histogram analysis shows that the plane and the quadric local surface modelling methods is the best methods to be used in the research where the 3D test object to be modelled contains curvy surfaces without sharp edges and corners.

Selection of an Algorithm for Assessing the Verticality of Complex Slender Objects Using Semi-Automatic Point Cloud Analysis

Remote technologies, including laser scanning, are frequently employed to acquire data describing the geometric condition of engineering objects. The automation of point cloud processing becomes essential for promptly and reliably monitoring changes in their current shape. The article introduces a methodology for generating point clouds, focusing on detecting the shape of the object’s cross profiles and subsequently determining its inclination through simulations and real data recorded using terrestrial laser scanning technology. The simulations enabled the identification of variations in the characteristics of changes in the course of the axis of a slender structure, depending on the adopted calculation method. Point clouds derived from measurements of complex engineering objects facilitated the validation of the assumptions of the proposed methodology. The suggested solution enables the semi-automatic extraction of data from point clouds and the assessment of the geometric state of engineering object axes based on multi-temporal point clouds.

Comparison of TLS and SLAM technologies for 3D reconstruction of objects with different geometries

Technological advances have made the 3D mapping process easily available and simpler. However, there are still aspects that need to be improved and enhanced. The efficient acquisition of 3D data and reconstruction of objects with high accuracy continues to be a challenge for the scientific community. One of the most frequently used 3D mapping methods is Terrestrial Laser Scanning (TLS), which allows the collection of high-resolution and precise data. Another method gaining popularity among researchers and professionals is mobile scanning technology, which enables real-time data capture. Its mobility and speed make it an effective alternative to traditional scanning technologies. This article compares two mapping technologies: SLAM (Simultaneous Localization and Mapping) and TLS taking into account the technical aspects of the instruments, processing methods, time and cost, and concluding with an assessment of the final accuracy. The geometry of several selected objects was analyzed. The resulting root mean square error (RMSE) for the compared distances on the two point clouds was 5 cm, which proves that the SLAM technology can be successfully applied for scenarios requiring centimeter-level accuracy.

Measurement of the Bijambare Cave Using the Terrestrial Laser Scanning Method

The article explores the methods and potential applications of terrestrial laser scanning technology. It also presents the preliminary results of scanning the Bijambare cave, where a georeferenced three-dimensional model of the cave's interior was created. This model, based on available data, stands as the first accurate 3D representation of a speleological object in Bosnia and Herzegovina. The first section of the paper provides a brief overview of the Bijambare cave area and the laser scanning technology employed, highlighting its advantages over other geodetic measurement techniques. Subsequently, the text delves into the stages of the measurement processing, followed by an examination of the various products generated. The practical significance of these products is illustrated using the example of the Bijambare cave.

Construction of a digital twin model for vertical storage tank deformation assessment using terrestrial laser scanning technology

The foundational settlement and deformation of vertical storage tanks are crucial factors influencing their safe operation. To enable rapid deformation assessment of storage tanks, this paper combines point cloud data acquired through terrestrial laser scanning with relevant data processing algorithms to construct a digital twin (DT) model. This achieves high-precision automated detection of tank deformation, facilitating the digital transformation of deformation assessment and offering an integrated detection strategy. First, Euclidean distance clustering is applied to the point cloud, and the point density within clusters is statistically analyzed using a Gaussian distribution. This results in a collection of point clusters within one standard deviation, effectively filtering out outliers and noise points, which facilitates the rapid global registration of the point cloud. Second, in order to quickly segment tank point clouds in the scene, back propagation neural network classification learning based on principal component analysis information is used. The point cloud model is combined with the fitting information of slices to generate a DT model, whose deformation can be evaluated through comparison with appropriate storage tank specifications, taking radial deformation, tank inclination, and foundation settlement as indicators.

Exploring the influence of tree species richness on vertical structure variability in young plantations using terrestrial laser scanning

Forest structure spatially varies at the landscape-scale (between-plot) but also local-scale (within-plot). Both scales of structural variability have significant impacts on forest ecosystem functioning and stability. However, we still have a limited understanding of how tree species richness affects the spatial structural variability. In this study, we disentangled within- and between-plot variability in stand structural variables depending on tree species richness level. Terrestrial laser scanning (TLS) technology, capable of developing forest vertical structure in 3D detail, was applied in the FORBIO tree diversity experiment at three sites in Belgium. One site was 9-year old (Hechtel-Eksel) and other two sites were 11-year old (Zedelgem and Gedinne). Each site included five different sets of one, two, three, and four tree species mixtures with one replica. At each plot, four single scan locations were used. Six stand structural variables were quantified based on TLS vertical plant profiles. We hypothesized that within-plot structural variability would increase with species richness, but that the between-plot structural variability would decrease with species richness. Our study revealed notable differences in structural variability between monocultures and mixtures across all sites examined. However, the relationship between tree species richness and structural variability patterns is site-dependent. Specifically, at the Zedelgem site, we observed increased within-plot variability and decreased between-plot variability with species richness, supporting the hypothesis that species richness drives stand structural variability. However, the hypothesized pattern was not as strong at the Hechtel-Eksel and Gedinne sites. Moreover, the various structural variables displayed contrasting responses to changes in species richness. These findings indicated the potential influence of tree species richness on within- and between-plot structural variability in young plantations, particularly in favorable site conditions with well-adapted species pools. Hence, afforestation measures would benefit from planting multiple tree species to initiate structurally complex stands by considering species richness level.

A Pre-Procession Module for Point-Based Deep Learning in Dense Point Clouds in the Ship Engineering Field

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

Horizontal viewsheds of large herbivores as a function of woodland structure

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

An Automated Pipeline for Extracting Forest Structural Parameters by Integrating UAV and Ground-Based LiDAR Point Clouds

In recent times, airborne and terrestrial laser scanning have been utilized to collect point cloud data for forest resource surveys, aiding in the estimation of tree and stand attributes over hectare-scale plots. In this study, an automated approach was devised to estimate the diameter at breast height (DBH) and tree height across the entire sample area, utilizing information acquired from terrestrial laser scanning (TLS) and airborne laser scanning (ULS). Centered around a meticulously managed artificial forest in Northern China, where Mongolian oak and Chinese Scots pine are the predominant species, both TLS and ULS operations were conducted concurrently on each plot. Subsequent to data collection, a detailed processing of the point cloud data was carried out, introducing an innovative algorithm to facilitate the matching of individual tree point clouds from ULS and TLS sources. To enhance the accuracy of DBH estimation, a weighted regression correction equation based on TLS data was introduced. The estimations obtained for the Chinese Scots pine plots showed a correlation of R2 = 0.789 and a root mean square error (RMSE) of 3.2 cm, while for the Mongolian oak plots, an improved correlation of R2 = 0.761 and a RMSE of 3.1 cm was observed between predicted and measured values. This research significantly augments the potential for non-destructive estimations of tree structural parameters on a hectare scale by integrating TLS and ULS technologies. The advancements hold paramount importance in the domain of large-scale forest surveys, particularly in the calibration and validation of aboveground biomass (AGB) estimations.

Design Improvement for a Maritime Training Polygon using 3D Terrestrial Laser Scanning Technology

In the current geo-strategic context, the North Atlantic Treaty Organization (NATO) and the International Maritime Organization (IMO) impose increasingly high standards for seafarers' preparation in the ship's vitality training centers (elaborate constructions, designed and equipped specifically for training personnel in scenarios involving flooding and fires that may occur on board ships). The buildings housing these training areas experience considerable mechanical and thermal stress, which, over time, affects their structural integrity. Therefore, repairs and modernization work become necessary. This paper provides a case study on the application of technologies for terrestrial laser scanning of buildings, with a focus on the vitality training polygon. The originality of the approach comes from achieving "as-built" documentation for the vitality polygon using 3D laser scanning technology. This includes both three-dimensional modeling based on digital information from the scanning process, as well as structural analysis using finite element techniques for the buildings where crew training takes place. The study also analyzes the distribution of total deformations and stresses in the walls of exercise compartments for flooding and water fight scenarios. Moreover, temperature distribution in the walls and interior atmosphere of these compartments is examined for fire scenarios and firefighting.

Discrimination of Leaves in a Multi-Layered Mediterranean Forest through Machine Learning Algorithms

Terrestrial laser scanning (TLS) technology characterizes standing trees with millimetric precision. An important step to accurately quantify tree volume and above-ground biomass using TLS point clouds is the discrimination between timber and leaf components. This study evaluates the performance of machine learning (ML)-derived models aimed at discriminating timber and leaf TLS point clouds, focusing on eight Mediterranean tree species datasets. The results show the best accuracies for random forests, gradient boosting machine, stacked ensemble model, and deep learning models with an average F1 score equal to 0.92. The top-performing ML-derived models showed well-balanced average precision and recall rates, ranging from 0.86 to 0.91 and 0.92 to 0.96 for precision and recall, respectively. Our findings show that Italian maple, European beech, hazel, and small-leaf lime tree species have more accurate F1 scores, with the best average F1 score of 0.96. The factors influencing the timber–leaf discrimination include phenotypic factors, such as bark surface (i.e., roughness and smoothness), technical issues (i.e., noise points and misclassification of points), and secondary factors (i.e., bark defects, lianas, and microhabitats). The top-performing ML-derived models report a time computation ranging from 8 to 37 s for processing 2 million points. Future studies are encouraged to calibrate, configure, and validate the potential of top-performing ML-derived models on other tree species and at the plot level.

Individual tree volume estimation with terrestrial laser scanning: Evaluating reconstructive and allometric approaches

Accurate estimates of above-ground tree biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data. Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, which can be converted to biomass with wood basic density. Existing TLS-based approaches range from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories. In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM). Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total wood, stem, coarse wood and fine branch volume. We observe similar accuracy in merchantable (¿7 cm) wood compartments for ASMs (NRMSE = 25 %) and QSMs (NRMSE = 29 %), with QSMs showing better results for broadleaves than conifers and generally overestimating fine branch volume. Feature selection shows that a combination of stem diameters and volume of convex hulls around tree crowns has the most potential to model the entire tree volume including branches, especially for conifers. In cases where the quality of available point clouds is insufficient for QSMs, 3D information can thus still be utilised by deriving geometric parameters. The integration of crown dimension parameters into new allometric models could substantially improve the estimation of branch wood volume.

Interactive Thematic Map as a Means of Documenting and Visualizing Information about Cultural Heritage Objects

Technological progress in recent decades has made it possible to develop the process of documentation and visualization of cultural heritage objects. Despite numerous studies dealing with the documentation of cultural heritage objects, no standardized research methodology has yet been developed in this field. The interest of many specialists from different fields carrying out different work related to the documentation of cultural heritage objects has resulted in a large amount of data, which causes problems in its processing and visualization. As a rule, researchers focus on one method of data collection and, consequently, on one type of data visualization. The documentation of cultural heritage is very important. Therefore, the authors of this article have aimed to develop a methodological data collection process for the documentation and visualization of information about cultural heritage objects. This is particularly important in light of the development of new methods of measuring and inventorying cultural heritage objects, such as laser scanning or low-level aerial photogrammetry. The authors recognize the need to systematize the methodology of collecting and processing data on cultural heritage objects. In addition, it is critical to develop a methodology for visualizing the acquired data using terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) technology. One of the most important assumptions of the article is to have universally understandable information about the object. The type of documentation and visualization of information developed in the article will be an interactive thematic map (using Leaflet.js and Three.js). Such a map will allow to collect and visualize all kinds of data, from attribute data to 3D models.

3D model of the Turka quarry

The aim of this work is to study the Turka quarry using terrestrial laser scanning, as well as to build a 3D model of the object. Method. The study of the outcrop was carried out with terrestrial laser scanning. The article describes the principles of operation of laser sensors and provides a classification of error sources. It also emphasizes the importance of achieving the maximum accuracy specified by scanner manufacturers. The location of the researched object. The studied quarry is located on the northern outskirts of the city of Turka, Lviv region. From the geological point of view, the object is situated in the Outer Ukrainian Carpathians that belong to the Carpathian mountain system. The inactive quarry is structurally confined to the north-western part of the Krosno nappe of the Ukrainian Carpathians. The characteristic Turka (Krosno) type of cross-section of the Oligocene-Miocene age is exposed in the walls of the quarry. This is a layering of massive packs of gray fine-grained sandstones with argillites and siltstones which are broken with joints. The joints are filled with longitudinal, transverse and differently oriented veins. They are often wedged out. Their thickness ranges from a few mm to 55 mm or more. Slickensides and leaching are observed along the cracks. The research results make it possible to analyze the geological structure without being directly near the object. The paper provides a workflow diagram of the terrestrial scanning workflow. This includes object reconnaissance, establishing and determining the coordinates of reference and control points. It also involves performing terrestrial 3D scanning, photographing an object, creating a cloud of points based on laser scanning data, developing a mash model based on point clouds and digital images. The accuracy of the mash model was defined by comparison of the coordinates of the control points obtained from the mash model and tacheometric survey. The absolute spatial difference does not exceed five centimeters. The scientific novelty and practical significance are in the creation of a virtual model of the Turka quarry. For the first time, terrestrial laser scanning technology was used for the research of this object. As a result, a 3D model was obtained, which can be used for further research in the field of geology, in particular structural geology, sedimentology, mineral reserve calculations and geotourism.

Terrestrial Laser Scanning for 3D Assets Registry

This study aimed to assess the feasibility of using terrestrial laser scanning (TLS) technology for creating 3D asset registries in facilities management. The research utilized a case study approach to scanning an industrial facility, and the resulting data was processed to create a 3D model of the assets. The study found that TLS technology can produce highly accurate and detailed 3D models of assets, which can aid in asset management and maintenance. However, the technology has some limitations, such as cost and the need for skilled operators. The study suggests that TLS technology can be a valuable tool for asset management and recommends further research in this area.

Static Terrestrial Laser Scanning (TLS) for Heritage Building Information Modeling (HBIM): A Systematic Review

Heritage Building Information Modeling (HBIM) is an essential technology for heritage documentation, conservation, and management. It enables people to understand, archive, advertise, and virtually reconstruct their built heritage. Creating highly accurate HBIM models requires the use of several reality capture tools, such as terrestrial laser scanning (TLS), photogrammetry, unmanned aerial vehicles (UAV), etc. However, the existing literature did not explicitly review the applications and impacts of TLS in implementing HBIM. This paper uses the PRISMA protocol to present a systematic review of TLS utilization in capturing reality data in order to recognize the status of applications of TLS for HBIM and identify the knowledge gaps on the topic. A thorough examination of the 58 selected articles revealed the state-of-the-art practices when utilizing static TLS technology for surveying and processing captured TLS data for developing HBIM models. Moreover, the absence of guidelines for using static TLS surveys for HBIM data acquisition, the lack of robust automated frameworks for producing/transferring 3D geometries and their attributes from TLS data to BIM entities, and the under-utilized application of TLS for long-term monitoring and change detection were identified as gaps in knowledge. The findings of this research provide stakeholders with a good grasp of static TLS for HBIM and therefore lay the foundation for further research, strategies, and scientific solutions for improving the utilization of TLS when documenting heritage structures and developing HBIM.