A Procedure to Obtain a 3D Model in Bim and Structural Analysis Software

Photogrammetric surveying using unmanned aerial systems (UAS) and structure from motion (SfM) is a rapidly emerging technique that has been widely used as a valuable research tool in geodesy and related disciplines. We studied surveying and three-dimensional (3D) modeling based on UAS and SfM. In particular, we focus on the accuracy and quality of UAS-SfM in 3D modeling and volumetric calculation of a building with an overhanging feature. For this purpose, two aerial surveys were performed using a fixed-wing and a multirotor aircraft with nadir and oblique camera axes. For validating the results, field surveys were carried out using terrestrial laser scanner (TLS), differential global navigation satellite system, and total station. To study the performance of SfM software on the accuracy and quality of point clouds, UAS images were processed using three software packages: Agisoft PhotoScan, Pix4Dmapper, and 3Dsurvey. As a result of photogrammetric image processing, 3D dense point clouds, mesh models, and digital surface models were generated. For validating the UAS-SfM results, the models were compared with the TLS model and field measurements; absolute accuracy assessments and model versus model comparisons were performed. The most accurate and high-quality 3D models comparable to TLS models were obtained from oblique images. PhotoScan generated relatively more accurate 3D models with the horizontal and vertical accuracy of root mean square error 0.025 and 0.02 m, respectively. The maximum discrepancies in dimensions and volume measurements from the UAS-SfM-derived point cloud were at the level of 0.01 m and 0.66 m3 (0.03%). The results highlighted that using a low-cost UAS and SfM photogrammetry, high-accuracy and high-quality 3D models can be generated. The results confirm that with respect to its rapid data acquisition and centimeter-level accuracy, UAS-SfM can be considered as a suitable alternative approach to conventional measurement techniques, especially in engineering and emergency response.

Abstract. Tourists and hikers visiting glaciers all year round face hazards such as sudden terminus collapses, typical of such a dynamically evolving environment. In this study, we analyzed the potential of different survey techniques to analyze hazards of the Forni Glacier, an important geosite located in Stelvio Park (Italian Alps). We carried out surveys in the 2016 ablation season and compared point clouds generated from an unmanned aerial vehicle (UAV) survey, close-range photogrammetry and terrestrial laser scanning (TLS). To investigate the evolution of glacier hazards and evaluate the glacier thinning rate, we also used UAV data collected in 2014 and a digital elevation model (DEM) created from an aerial photogrammetric survey of 2007. We found that the integration between terrestrial and UAV photogrammetry is ideal for mapping hazards related to the glacier collapse, while TLS is affected by occlusions and is logistically complex in glacial terrain. Photogrammetric techniques can therefore replace TLS for glacier studies and UAV-based DEMs hold potential for becoming a standard tool in the investigation of glacier thickness changes. Based on our data sets, an increase in the size of collapses was found over the study period, and the glacier thinning rates went from 4.55 ± 0.24 m a−1 between 2007 and 2014 to 5.20 ± 1.11 m a−1 between 2014 and 2016.

Abstract. Soil erosion is a decisive earth surface process strongly influencing the fertility of arable land. Several options exist to detect soil erosion at the scale of large field plots (here 600 m²), which comprise different advantages and disadvantages depending on the applied method. In this study, the benefits of unmanned aerial vehicle (UAV) photogrammetry and terrestrial laser scanning (TLS) are exploited to quantify soil surface changes. Beforehand data combination, TLS data is co-registered to the DEMs generated with UAV photogrammetry. TLS data is used to detect global as well as local errors in the DEMs calculated from UAV images. Additionally, TLS data is considered for vegetation filtering. Complimentary, DEMs from UAV photogrammetry are utilised to detect systematic TLS errors and to further filter TLS point clouds in regard to unfavourable scan geometry (i.e. incidence angle and footprint) on gentle hillslopes. In addition, surface roughness is integrated as an important parameter to evaluate TLS point reliability because of the increasing footprints and thus area of signal reflection with increasing distance to the scanning device. The developed fusion tool allows for the estimation of reliable data points from each data source, considering the data acquisition geometry and surface properties, to finally merge both data sets into a single soil surface model. Data fusion is performed for three different field campaigns at a Mediterranean field plot. Successive DEM evaluation reveals continuous decrease of soil surface roughness, reappearance of former wheel tracks and local soil particle relocation patterns.

The design of the civil engineering works in High Speed Two (HS2) is a good example of what can be achieved when the Building Information Modelling (BIM) process is embraced. Central to the BIM process is a three-dimensional (3D) model that communicates the civil design to enable construction, asset management, operation and maintenance in a fully collaborative and coordinated multi-disciplinary environment. Software developers of leading BIM packages have responded to the requirements of HS2 and similar projects by delivering feature-rich applications to enable design and BIM to go hand-in-hand. HS2, however, is under a tight programme to deliver a 3D model with a Level of Detail (LOD) beyond what has been required on most projects to date, and this has resulted in exhaustive testing of the software. Such requirements have identified gaps in the BIM software tools for drainage designers. Drainage designers utilise hydraulic modelling software to design and test their designs. This software must be efficient, reliable and, most importantly, have all the design tools necessary to design and test a drainage network to meet the client’s requirements. HS2 Ltd’s requirements under the Asset Data Dictionary Definition Document (AD4) are to provide spatially accurate 3D models along with detailed and relevant asset data. The integrated project team delivering the HS2 Area North works opted to achieve this by delivering fully attributed BIM models. However, software developers of leading drainage design packages do not have the BIM capabilities required to provide a BIM model with the LOD required in HS2 on their own. They must be integrated with a BIM software. This leaves drainage designers using two separate systems with a requirement to integrate two software packages to work seamlessly together in a BIM environment. To overcome this, a suite of tools was developed using Visual Basic for Applications (VBA) to convert from MicroDrainage (a drainage design tool) to Bentley OpenRoads Designer (a BIM package) and fully attribute the BIM models. The tools have been developed specifically for HS2 feature definitions and requirements, however, with further development, they could be customisable for use on other projects thus improving the level of detail, accuracy and efficiency future deliverables on future projects.

In the current modern era of information and technology, emerging remote advancements have been widely established for detailed virtual inspections and assessments of infrastructure assets, especially bridges. These technologies are capable of creating an accurate digital representation of the existing assets, commonly known as the digital twins. Digital twins are suitable alternatives to in-person and on-site based assessments that can provide safer, cheaper, more reliable, and less distributive bridge inspections. In the case of bridge monitoring, Unmanned Aerial Vehicle (UAV) photogrammetry and Terrestrial Laser Scanning (TLS) are among the most common advanced technologies that hold the potential to provide qualitative digital models; however, the research is still lacking a reliable methodology to evaluate the generated point clouds in terms of quality and geometric accuracy for a bridge size case study. Therefore, this paper aims to provide a comprehensive methodology along with a thorough bridge case study to evaluate two digital point clouds developed from an existing Australian heritage bridge via both UAV-based photogrammetry and TLS. In this regard, a range of proposed approaches were employed to compare point clouds in terms of points’ distribution, level of outlier noise, data completeness, surface deviation, and geometric accuracy. The comparative results of this case study not only proved the capability and applicability of the proposed methodology and approaches in evaluating these two voluminous point clouds, but they also exhibited a higher level of point density and more acceptable agreements with as-is measurements in TLS-based point clouds subjected to the implementation of a precise data capture and a 3D reconstruction model.

In recent years, low-cost unmanned aerial vehicles (UAVs) photogrammetry and terrestrial laser scanner (TLS) techniques have become very important non-contact measurement methods for obtaining topographic data about landslides. However, owing to the differences in the types of UAVs and whether the ground control points (GCPs) are set in the measurement, the obtained topographic data for landslides often have large precision differences. In this study, two types of UAVs (DJI Mavic Pro and DJI Phantom 4 RTK) with and without GCPs were used to survey a loess landslide. UAVs point clouds and digital surface model (DSM) data for the landslide were obtained. Based on this, we used the Geomorphic Change Detection software (GCD 7.0) and the Multiscale Model-To-Model Cloud Comparison (M3C2) algorithm in the Cloud Compare software for comparative analysis and accuracy evaluation of the different point clouds and DSM data obtained using the same and different UAVs. The experimental results show that the DJI Phantom 4 RTK obtained the highest accuracy landslide terrain data when the GCPs were set. In addition, we also used the Maptek I-Site 8,820 terrestrial laser scanner to obtain higher precision topographic point cloud data for the Beiguo landslide. However, owing to the terrain limitations, some of the point cloud data were missing in the blind area of the TLS measurement. To make up for the scanning defect of the TLS, we used the iterative closest point (ICP) algorithm in the Cloud Compare software to conduct data fusion between the point clouds obtained using the DJI Phantom 4 RTK with GCPs and the point clouds obtained using TLS. The results demonstrate that after the data fusion, the point clouds not only retained the high-precision characteristics of the original point clouds of the TLS, but also filled in the blind area of the TLS data. This study introduces a novel perspective and technical scheme for the precision evaluation of UAVs surveys and the fusion of point clouds data based on different sensors in geological hazard surveys.

The accurate estimation of tree attributes is essential for sustainable forest management. Terrestrial Laser Scanning (TLS) is a viable remote sensing technology suitable for estimating under canopy structure. However, TLS measurements generally underestimate tree height in taller trees, which leads to the underestimation of other tree attributes (e.g., stem volume). The integration of information derived from TLS and Unmanned Aerial Vehicle (UAV) photogrammetry could potentially improve tree height estimation. This study investigated the applicability of integrating TLS and UAV photogrammetry to estimate individual tree attributes in managed coniferous forests of Japan. Diameter at breast height (DBH), tree height, and stem volume were estimated by (1) TLS data only, (2) integrating TLS and UAV data with TLS tree locations, and (3) integrating TLS and UAV data with treetop detections of the tree canopy. The TLS data only approach achieved high accuracy for DBH estimations with a root mean squared error (RMSE) of 2.36 cm (RMSE% 5.6%); however, tree height was greatly underestimated, with an RMSE of 8.87 m (28.9%) and a bias of −8.39 m. Integrating TLS and UAV photogrammetric data improved tree height estimation accuracy for both the TLS tree location (RMSE of 1.89 m and a bias of −0.46 m) and the treetop detection (RMSE of 1.77 m and a bias of 0.36 m) approaches. Integrating TLS and UAV photogrammetric data also improved the accuracy of the stem volume estimations with RMSEs of 0.21 m3 (10.8%) and 0.21 m3 (10.5%) for the TLS tree location and treetop detection approaches, respectively. Although the tree height of suppressed trees tended to be overestimated by TLS and UAV photogrammetric data integration, a good performance was obtained for dominant trees. The results of this study indicate that the integration of TLS and UAV photogrammetry is beneficial for the accurate estimation of tree attributes in coniferous forests.

Abstract. The transmission main-intake isoneof the most important units to supply the electricity in some place. Each transmission main-intake has its own utilities and assets according to each function and type. During this time, each transmission main-intake structure and the assets inside only canbe monitored by 2-dimensional (2D) model other than on-site visits. This study is conducted to produce a 3-dimensional (3D) model of the building's internal structure and assets that will facilitate and further improves the monitoring process, maintenance and documentation of assets for certain parties for further uses in form of 3D Building Information Modelling (BIM). This study was conducted in Tenaga Nasional Berhad (TNB) control and relay room at PE61 132/22KV Transmission main-intake building of Universiti Teknologi Malaysia (UTM) using Terrestrial Laser Scanner (TLS) Topcon GLS-2000 model. At the data processing stage, several series of software was used to complete the 3D model. Scanning process will generate an indoor point cloud of the building. The result from the data processing stage is more focused on the 3D internal model of the building that has been digitized from the point cloud data. The 3D model will be able to show the internal structure of buildings and the assets more clearly. In order to complete the 3D BIM, information regarding the assets was added. In this study, the efficiency of TLS Topcon GLS-2000 for 3D BIM was determined in term of its accuracy by comparing with the distometer. The accuracy for scanned data from TLS were compared with the distometer by using root mean square error (RMSE) formula, and the accuracy is only ±0.004 m.

This paper aims to compare models from terrestrial laser scanning (TLS), terrestrial photogrammetry (TP), and unmanned aerial vehicle photogrammetry (UAVP) surveys to evaluate their potential in cliff erosion monitoring. TLS has commonly been used to monitor cliff-face erosion (monitoring since 2010 in Normandy) because it guarantees results of high precision. Due to some uncertainties and limitations of TLS, TP and UAVP can be seen as alternative methods. First, the texture quality of the photogrammetry models is better than that of TLS which could be useful for analysis and interpretation. Second, a comparison between the TLS model and UAV or TP models shows that the mean error value is mainly from 0.013 to 0.03 m, which meets the precision requirements for monitoring cliff erosion by rock falls and debris falls. However, TP is more sensitive to roughness than UAVP, which increases the data standard deviation. Thus, UAVP appears to be more reliable in our study and provides a larger spatial coverage, enabling a larger cliff-face section to be monitored with a regular resolution. Nevertheless, the method remains dependent on the weather conditions and the number of operators is not reduced. Third, even though UAVP has more advantages than TP, the methods could be interchangeable when no pilot is available, when weather conditions are bad or when high reactivity is needed.

Nowadays precast concrete elements are widely used in buildings, bridges, and other civil infrastructure facilities because precast elements allow rapid construction and high precision quality control. However, the quality inspection of precast concrete elements primarily relies on manual inspection, which is time consuming and error-prone. Recently, terrestrial laser scanner (TLS) has been used to improve quality inspection. The authors’ group has previously developed an automated dimension estimation technique for precast concrete elements, but its applicability is limited only to precast elements with rectangular shapes. This study advances our previous work so that the dimensions of precast elements with irregular shapes can also be automatically estimated. First, a density-based clustering algorithm is adopted to extract target objects from 3D point cloud data acquired by a TLS. Then, coarse registration is conducted to match each object extracted from the 3D point cloud with the asdesign objects in building information models (BIM) one by one. Thirdly, all point cloud data points are registered onto different surfaces of the as-designed objects in BIM through fine registration. Lastly, the as-built dimensions of the precast concrete element are extracted and compared with the as-design ones in BIM. The effectiveness and accuracy of the developed technique are examined using point cloud data obtained from a laboratory-scale precast concrete bridge deck panel.

Architectural heritage surveying plays a fundamental role in the preservation of historic buildings for scientific research, education and tourism. The use of Unmanned Aerial Vehicles and Terrestrial Laser Scanning techniques are essential for architectural heritage surveying and mapping. In recent years, the combination of Building Information Modelling (BIM) with heritage studies has been presented as Historic BIM (HBIM) which, integrated with UVA and TLS, is a technique that is able to deal more efficiently with the management and protection of historic buildings. This paper focuses on the integration of UVA images and point clouds from laser scanning to build a 3D architectural model for the documentation of Chinese historic buildings. In particular, the method, tested in the case study of the traditional village, Hexinwu, China, can contribute further to the analysis, evaluation and heritage planning of this remarkable architectural structure, thus increasing its historical significance for the future.

Abstract. UAV (Unmanned Aerial Vehicle) photogrammetry, which combines UAV and freely available internet-based 3D modeling software, is widely used as a low-cost and user-friendly photogrammetry technique in the fields such as remote sensing and geosciences. In UAV photogrammetry, only the platform used in conventional aerial photogrammetry is changed. Consequently, 3D modeling software contributes significantly to its expansion. However, the algorithms of the 3D modelling software are black box algorithms. As a result, only a few studies have been able to evaluate their accuracy using 3D coordinate check points. With this motive, Smart3DCapture and Pix4Dmapper were downloaded from the Internet and commercial software PhotoScan was also employed; investigations were performed in this paper using check points and images obtained from UAV.

Abstract. Nowadays, the necessity of heritage documentation is essential for monitoring, maintenance, and understanding needed for conservation. The survey phase has been considerably improved using cutting-edge technologies such as Unmanned Aerial Vehicles (UAV) and Terrestrial Laser Scanners (TLS). Both of these technologies have been applied in heritage documentation individually or combined. Heritage documentation in a post-natural disaster is a situation that requires rapid data acquisition on a hazardous field. On 12th of June 2017 an earthquake (Mw = 6.3), south of Lesvos island, Greece occurred, which was devastating for the Vrisa village destroying, among many other buildings the main church. The Greek State decided from the first moment to restore the whole village, which was proclaimed as a “traditional settlement” since 2002, in its original place starting from the church and the school due to the symbolic meaning that those have to a local community. For this purpose, a 3D model of the church was requested by the authorities for damage assessment. In this paper TLS and UAV photogrammetry has been used in an integrated design to rapidly facilitate the acquisition of the whole church, eliminating all possible occlusions. The TLS was exploited for the acquisition of the facades while the UAV was used for the acquisition of the roof. The recent improvement of the post-processing algorithms provided the ability to implement the fusion of TLS and UAV models and deliver an accurate 3D model of the whole church the same day that the survey was conducted.

The construction industry increasingly relies on digital twins and building information modeling (BIM) to streamline project management; however, the discrepancy between the as-designed model and the as-built state remains a critical source of cost overruns and structural failures. This paper proposes a robust, automated framework for construction quality assessment (CQA) and progress monitoring by integrating multi-view stereo (MVS) 3D reconstruction with semantic BIM alignment. Unlike traditional manual inspections or expensive terrestrial laser scanning (TLS) methods, our approach utilizes cost-effective unmanned aerial vehicle (UAV) imagery to generate high-density point clouds. We introduce a novel semantic-aware registration pipeline that leverages deep learning-based segmentation to align noisy reconstruction data with pristine BIM geometries, effectively mitigating the challenges posed by dynamic construction environments and varying lighting conditions. By calculating the Euclidean deviations between the reconstructed mesh and the BIM elements, the system automatically classifies construction components into accurate, deviated, or missing categories. Experimental validation on complex high-rise construction datasets demonstrates that the proposed method achieves sub-centimeter accuracy in deviation detection and significantly outperforms conventional Iterative Closest Point (ICP) variations in alignment robustness. The results suggest that this pipeline can substantially reduce inspection latency and facilitate proactive decision-making in large-scale infrastructure projects.

For quickly predicting the rational arrangement of catalysts and substrates, we previously proposed a method to calculate the interacted volumes of molecules over their 3D point cloud models. However, the nonuniform density in molecular point clouds may lead to incomplete contours in some slices, reducing the accuracy of the previous method. In this paper, we propose a two-step method for more accurately computing molecular interacted volumes. First, by employing a prematched mesh slicing method, we layer the 3D triangular mesh models of the electrostatic potential isosurfaces of two molecules globally, transforming the volume calculation into finding the intersecting areas in each layer. Next, by subdividing polygonal edges, we accurately identify intersecting parts within each layer, ensuring precise calculation of interacted volumes. In addition, we present a concise overview for computing intersecting areas in cases of multiple contour intersections and for improving computational efficiency by incorporating bounding boxes at three stages. Experimental results demonstrate that our method maintains high accuracy in different experimental data sets, with an average relative error of 0.16%. On the same experimental setup, our average relative error is 0.07%, which is lower than the previous algorithm's 1.73%, improving the accuracy and stability in calculating interacted volumes.