Integrating wooden altarpieces into H-BIM: Geometric profiling, complex artworks, and digital heritage mapping

Integrating wooden altarpieces into H-BIM: Geometric profiling, complex artworks, and digital heritage mapping Juan Moyano * , Eva Martínez, Juan E. Nieto-Juli´ an, María Fern´ andez-Alconchel University of Seville, Department of Graphical Expression and Building Engineering, Ave.Reina Mercedes, 4A, 41012 Seville, Spain ARTICLE INFO Keywords: HBIM Photogrammetry TLS Baroque altarpiece Mesh to BIM Geometrics surfaces Parametric tools ABSTRACT In the study and conservation of Cultural Heritage, various disciplines contribute to the research aimed at extracting information from both historical objects and heritage buildings. The contribution of this work is part of an interdisciplinary process to model, register, and evaluate complex models of knowledge. Evaluate a complex model, where there are works of art made of wood, painting, and sculpture. The results demonstrate a process of analysis and geometric characterisation of the shapes, in which most of the profiles are worked with a new methodology of the Best Fit Model (BFMP), and in which its analysis represents a deviation between a range of 7 and 9 mm. The development of low-relief models is based on the Poisson reconstruction equation, applied through a variable workflow using multiple software tools. Furthermore, an Entity Information Matrix (EIM) is introduced, enhancing the exchange and classification of architectural data. This study supports the integration of real-world 3D scans into BIM environments, providing a replicable model particularly suited for the digitization of altarpieces and façades. 1. Introduction The In the conservation of Cultural Heritage, various disciplines converge to extract valuable information from historical objects and heritage buildings. Within the broader context of territorial, social, and cultural development—the three main pillars supporting built heritage—the Fourth Industrial Revolution is emerging, marked by transformative intelligent manufacturing processes and digitalization. This transformation is driven by the integration of new technologies such as the Internet of Things, big data, reverse engineering, and artificial intelligence. The objective goes beyond the mere creation of 3D digital replicas; the true value lies in integrating restoration projects—such as altarpieces—into BIM models, with the goal of reinforcing cultural identity and fostering new spaces for development. Reverse engineering and the Scan-to-BIM methodology present multiple challenges, positioning current advancements in Heritage Building Information Modelling (HBIM) at the center of the cultural and scientific discourse. 1.1. Introduction general The complexity of the process in the conservation of cultural assets means that new perspectives for studies and implementations are constantly being formulated to achieve UNESCO recommendations; to protect landscapes, natural and man-made environments, that are of cultural or aesthetic interest or that form a harmonious natural whole [1]. All these recommendations are made with the perfect technique to achieve the proposed objectives, namely that Cultural Heritage (CH) is a a substantial and dynamic knowledge deposit, considered a unique and irreplaceable source of aesthetic, historical, and cultural values [2] and a community mission that should therefore be documented to avoid the loss of objects and their history. Consequently, the works inserted in an architectural context are recognized as a world category and constitute in themselves fields of work of universal value. The architectural heritage made up of buildings, civil structures, and objects that are part of these structures is part of this unique value by nature. There are three determining factors to establish whether a cultural asset is worthy of being classified as heritage; its the historical, aesthetic, and architectural importance [3], although in other scientific readings there are other statements that establish integrity and context, * Corresponding author. E-mail addresses: [email protected] (J. Moyano), [email protected] (E. Martínez), [email protected] (J.E. Nieto-Juli´ an), [email protected] (M. Fern´ andezAlconchel). Contents lists available at ScienceDirect Automation in Construction journal homepage: www.elsevier.com/locate/autcon https://doi.org/10.1016/j.autcon.2025.106213 Received 4 January 2024; Received in revised form 14 April 2025; Accepted 15 April 2025 Automation in Construction 175 (2025) 106213 Available online 23 April 2025 0926-5805/© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). as additional relevant factors. In this field, the conservation of Architectural Heritage (AH) is a process of knowledge, management and improvement to preserve historical complex buildings [4]. Generally, both lowand high-relief sculptures (low relief refers to figures that protrude slightly from the surface of the background, while high relief refers to figures that project considerably outwards), as well as pictorial elements, are inserted in that architectural context, for example, tombs, altarpieces, and friezes among other artistic works. There are two important factors in the scientific recognition of a work of art, i) geometric documentation considered an essential tool for archaeologists and historians, since it reflects the dimensional reality of the object at levels of millimetric precision, and ii) the mechanisms for cataloguing cultural goods. The basic operational instrument for acquiring knowledge of heritage is the inventory, a mechanism that facilitates the management and protection of cultural assets [5]. For their part, catalogues require a higher level of knowledge since they imply research, an element that begins with the development of the inventory. Geometric information is acquired with Massive Data Capture Techniques (MDCS) using topographic instruments. The 3D digital reconstruction is acquired through the software that implements the geodetic measurements and processes the digital models. The important question is the unification between cataloguing procedures and their integration into digital replicas of works of art. Multimedia technologies developed at the end of the 1980s have favoured the construction of digital models, both for archaeology and architecture, and have benefited from these digital resources to improve heritage management and dissemination processes. One of the main applications of multimedia technologies is 3D recording as a documentation mechanism. In fact, there are institutions at the European level such as DIGITALEUROPE [6] that enthusiastically welcome that, in the planning process of heritage works, a digital version of the project should be delivered before it is built and the physical artefact must be a Digital Twin (DT). In this context, the meaning of the term Digital Twin has to do with a geometric replica where its potential deals with the monitoring and control of assets with semantic model structures. Let us not forget that the main components of the DT are considered to be; physical components, virtual models, and the data that connect them [7]. The fusion of DT is to predict and optimize performance and for this, simulation methods or data-based methods can be used [8]. The connection between BIM and DT could focus on the ability of BIM to structure itself in semantic models. This position opens a new scenario when it comes to working with heritage objects, with an approach from construction in the area of rehabilitation, architectural and sculptural restoration to industry spaces that respond to a new knowledge gap. 1.2. State of the art in digital technologies for altarpieces Protection and conservation are two sets of actions that aim at the sustainability and durability of cultural assets. The 2030 Agenda for Sustainable Development constitutes an action plan in its three dimensions: economic, social, and environmental. Cultural heritage according to UNESCO’s specifications can contribute to this sustainable development. Both monuments and cultural assets identify society, explaining its historical trajectory [9] and recognising the heritage of its generations. In this way, within the conservation process, geometric analysis plays a key role in protecting historic real estate assets. For example, in the case of painted vaults, their morphology and its chromatic characterisation are essential for restoration [10]. The other aspect is to document cultural assets in such a way that they endure over time. Digitisation is becoming one of the most important vehicles for preserving and protecting heritage assets. To this question, UNESCO [11] defines the term digital heritage as the set of computer materials of lasting value that must be preserved for future generations. However, in the field of practice, we must consider that digital technologies do not have the sole objective of documenting buildings. The application of Heritage Building Information Modelling (HBIM) processes provides an additional element compared to documentation alone, that is, the ability to follow an asset in continuous evolution and at the same time support interventions on it. Digital technologies help in their various fields to survey, diagnose, and disseminate architectural heritage. From this, the essence of digital works that also relate to heritage assets must also be preserved. We refer to the importance of obtaining records through point clouds after the tragic accident at Notre Dame Cathedral, where Andrew Tallon worked as a professor of medieval art documenting the content of the same work [12]. Thus, remote sensing techniques such as the Light Detection and Ranging (LiDAR) system and Structure from Motion (SfM) image capture techniques allow the surface of reality to be captured exhaustively and accurately. From the overview established by remote sensing techniques carried out by Bassier et al. [13]. A case study in the Bijloke church combined the technique of Terrestrial Laser Scanning (TLS) and SfM to document the paintings and ornaments of an altarpiece. In addition, Cantos Martínez et al. [14] used photogrammetry as a data acquisition technique to document and project the artistic work. Likewise, D´ avila [15] worked on photogrammetric restitution and an approximation to the digital image of altarpieces, specifically in the Church of San Jacinto (Venezuela). On the other hand, Hanke et al. [16] from an experimental campaign by TLS worked on the geometric projections of an altar to verify the contours of the elements and made a simplification of the altarpiece structures in 3D. In this line, most of the implementation works that have to do with Building Information Modelling (BIM) applied to heritage use LiDAR techniques to capture the geometry. The term “Scan to BIM” has been widely used, to generate vault structures [17], or to document structural analysis evaluations using finite element models [18]. This term has a specific meaning of the applicability of geometric shapes to the BIM platform, in the case of manual use [19,20], where no type of segmentation algorithm is applied, to another form called semi-automatic, focused on obtaining objectsin architecture [21] or engineering [22] or with algorithm procedures compatible with BIM platforms such as ArchiCAD+Grasshopper [23]. The concept between LiDAR-BIM, is also another term that unites the precise data techniques with 3D reconstruction modelling and then exports them to Revit software [18]. In this context, researchers are growing interested in addressing digital tools through methodologies that implement reverse engineering in historic buildings. For tangible and architectural cultural assets, Murphy et al. [24] carried out the first investigations on the information modelling of historical buildings from architectural patterns, with the construction of parametric objects. Oreni et al. [25] developed with a database of church objects such as stone vaults and wooden roof structures. In reality, few works are dedicated to showing in a comprehensive way the processes that a real estate (such as an altarpiece) has to go through until a 3D model can be obtained with semantic information about the restoration undergone in current times. The dissemination of accurace models allows knowledge of the object of study, thus GarcíaLe´ on et al. [26] experimented with a baroque altarpiece in the chapel of Our Father Jesus Nazarene of Cartagena applying multimedia techniques for 3D visualisation, the main objective being to combine techniques to obtain reliable documentation. Instead, Nieto et al. [27] worked on a TeamWork implementation project for the management and sustainability of real estate. Specifically, the variability of paintings that appear in the sacristy of the Church of the Company of Jesus in Quito is labelled. But until now there is a total absence of studies dedicated to structuring work on movable property using BIM technology. The importance of altarpieces as movable objects is based on the fact that they appear configured as architectural structures, and as containers for important artistic works of pictorial, sculptural style in various modalities, that is, in low, medium, and high relief, and the materials used in them are generally constructive pieces of wood. The 3D modelling of these structures on a BIM platform is a challenge in the field of architectural and archaeological heritage research. J. Moyano et al. Automation in Construction 175 (2025) 106213 2 1.3. Objectives. The challenge of bringing to BIM, altarpiece real estate The altarpieces are architectural structures that have occupied a stage assembly space to surprise the faithful on their visit to religious temples. Their extension was given especially in the Baroque era when the economic resources of the church guaranteed an artistic work of this high level. The devotion to religious images occupied a priority setting in strategic places in the temple, such as the side chapels, the main altar, and annexes to the churches. Most of these artistic works were designed by older architects and masters, although in other cases, such as that of the painter Claudio Coello in the work of the Martyrdom of Saint Stephen, they collaborated in the layout of the altarpiece ornaments [28]. Bringing these structures to BIM is an important challenge, since it is necessary to structure the previous work on geometry modelling and data acquisition techniques and then train operators to become familiar with BIM platforms. To provide a detailed description of Scan to BIM procedures in this sector, it must be said that the objective essentially sought by point cloud processing is the quality of the geometric precision for the purposes of 3D reconstruction. On the one hand, the quality of the point cloud must be evaluated, but on the other hand, the quality of the BIM geometry created must be evaluated. The first part is developed in Section 2.3, where the differentiation between the two massive data acquisition techniques performed is established. The adoption of these TLS iG and SfM iG technologies contributes to the automation of processes developed in Section 3. Furthermore, the objective is to increase the quality of the point cloud to maximize precision and minimize the influence of operators. The comparison between the TLS iG and SfM iG technologies serves to avoid uncertainty in the obtained data set. On the other hand, BIM involves managing and generating physical representations of operational elements of a building [29], so it is convenient to extract the morphological characteristics –such as shapes and spatial dimensionsto bring them to BIM and incorporate semantic labels –identification of componentsthat will allow the classification of the elements. This process is carried out in Section 3.1 through the ICP algorithm using CloudCompare. Also, the active interconnection between operators that has been developed in section 3.2 as TeamWork development. The model in this phase is initial, but the characteristics are in place to start modelling. Previously, an identification of the characterisation of the profiles that make up the model was made. Achieving the best profile fit model is one of the innovative methodologies of this research developed in Section 3.3. This procedure involves extracting the main characteristics of the modelling of pieces that mostly make up the work of art, therefore, the challenge is double in the sense of monitoring a procedure that optimises the geometric result of a cornice or object in its continuous form. On the other hand, it performs a simplification of the geometry to improve the resources of the model. The following Section 3.4 deals with the challenging process of modelling the artworks and having them exported in a mesh to BIM. These are not mere game visualizations, but rather elements that allow data entry into the BIM software. Making a mesh optimal in the BIM environment is one of the challenges currently faced by the scientific community. Section 4 develops one of the most outstanding inventive procedures of this article, which is the entity information matrix. This is a proposal for an underlying model that, through the classification of architectural structures, allows any identification in an architectural framework. Next, in section 5, the HBIM project of an altarpiece work that integrates works of art made of wood, painting and sculpture, by the likes of Juan Martínez Monta˜ n´ es, is completely modeled with the aim of reinforcing new identities, records and new spaces, development in research. All these steps are reflected in the workflow in Fig. 1. From the BIM expert operators level, it is about the implementation of the model in the experimental development of the work. (See Table 1.) 2. Work methodology The study follows a multi-phased framework explained in Section 2.2 to assess the barriers to implementation in Scan-to-BIM processes. The process, which ranges from point cloud capture to parametric modelling in BIM, seeks to ensure metric accuracy and interoperability, while evaluating the effectiveness of each technique in representing organic and geometric elements. Comparing point clouds (TLS vs. SfM) using algorithms such as ICP in CloudCompare reveals their complementary advantages, laying the groundwork for future applications in cultural heritage. 2.1. Case study. The altarpiece by Martínez Monta˜ n´ es Juan Martínez Monta˜ n´ es was one of the great image makers of sculptural art in the Spanish golden age [30] and a personal friend of the Fig. 1. Workflow. J. Moyano et al. Automation in Construction 175 (2025) 106213 3 scholar and painter Francisco Pacheco [31]. He began in the Granada workshop of the master Pablo de Rojas as an apprentice in the artistic nucleus of this city. In 1588, at the age of twenty, he travelled to Seville, although no early sculpture by the sculptor is known [32]. His studies were formed by means of engravings of the most famous artistic works of the Italian Cinquecentistas, which offered so much influence to the Spanish Mannerists. He managed to establish the sculptural norms of western Andalusia during the entire Baroque period. It is documented that the design of the Altarpiece of San Juan Bautista was the work of Juan Martínez Monta˜ n´ es. The imagery, reliefs, and carver by the same author and Francisco de Villegas. The gilding of the altarpiece and the polychromy were in charge of Juan de Uceda Castroverde and the pictorial repertoire by the same author. Hired on 29 January 29, 1610, it was completed in 1622 [33]. Regarding the iconographic programme, the structure of the altarpiece is configured in five levels from the basement to the upper part of the attic. The pillar structures attached to the main plane are developed through Doric order columns with fluted shafts. The pictorial repertoire is made by means of thirteen paintings on tables and nine reliefs with different degrees of sculptural depth that represent the life of Saint John the Baptist 2 a). The dimensions of the altarpiece can be considered as a normal-sized altarpiece of 4.80 by 8.79 m represented in Fig. 2 b). 3. Materials and methods Any implementation in BIM requires a work phase to integrate the systematic process that ranges from scanning to the creation of the parametric digital 3D model. Once the entire 3D model has been built with its geometric properties, we proceed to insert the semantic structure in each of the elements, thus increasing the interoperability of the model with their respective semantic units. Although much of the work done in BIM is directed at heritage, its objectives are based on the contribution of knowledge and heritage management [34]. Researchers in this area of knowledge try to implement processes to make digital platforms profitable in the applicability of architectural and archaeological heritage. For this reason, integrated survey methodologies play an important role in the digitisation of complex objects such as the analysed, in this case, an altarpiece artistic work [35]. Hybrid data acquisition with the combination of TLS and SfM, where each of the technologies provides attributes with complementary properties to the point cloud, makes the process hybrid. For this reason, BIM operators must consider which methodologies are the most optimal to obtain a good design with effective performance in the BIM model. It is not understood the studies of BIM platforms, of modelling without system implementation. Each of the work phases requires geometric model procedures and analytical models that justify the best work option. In this experimental design, the following phases take place: i) capture through TLS, ii) capture through photogrammetry, iii) evaluation of the model to establish metric reliability objectives, iv) semiautomatic segmentation to structure the elements, v) classification of structures and elements, vi) meshing process for the organic pieces, vii) extraction of the profiles from the wooden structures, viii) BIM Table 1 Descriptive Statistics N total Standart deviation ( σ ) (m) Min. Distance (m) Max. Distance (m) Average distance (m) Sum (m) Median (m) Profiler_1 54 0.01036 −0.021 0.0182 3.04E+01 0.0164 −7.5E-4 Profiler_2 37 0.01024 −0.0093 0.0294 0.00755 0.2793 0.0114 Profiler_3 50 0.01383 −0.0195 0.0228 0.00652 0.3262 0.01165 Profiler_4 58 0.00796 −0.005 0.0208 0.00562 0.3262 0.00205 Profiler_5 58 0.01452 −0.0271 0.0137 −0.00132 −0.0765 0.0033 Profiler_6 58 0.00944 −0.0154 0.0156 0.00418 0.2426 0.0076 Fig. 2. a) Image on the left, altarpiece by Martínez Monta˜ n´ es from the Church of the Annunciation. b) Image on the right, scale representation of the altarpiece in a scalar image. J. Moyano et al. Automation in Construction 175 (2025) 106213 4 modelling using ArchiCAD software of the architectural pieces, ix) insertion of the figures in the frame of the altarpiece, and x) Insertion of project data through dynamic schemes. 3.1. Capture of the point-cloud records With the appearance of the new Personal Laser Scanning (PLS) type geomatic technology equipment, which simplifies data capture and the manageability of records in architectural spaces, it was decided to carry out a first survey through BLK360 that uses Waveform Digitalisation Technology (WFD), with a maximum scanning speed of 360.000 points/ s. It has three HDR digital cameras with colour sensor and fixed focal length (single image 2592 ×1944 pixels, 60◦×45◦(vx hz), full-dome scanning of 30 images and automatic gap rectification, 150 Mpx, 360◦×300◦), as well as an infrared thermal camera (160 ×120 pixel single image, 71◦×56◦(vx hz), 10-image full-dome scan, 360◦×70◦), all four included in the kit. This instrument achieves a range accuracy according to the manufacturer of 4 mm at 10 m, and 7 mm at 20 m [36]. The result obtained is a point cloud of 2.651.440 points. The use of two massive data acquisition techniques allows us to guarantee that the entire surface of the altarpiece is covered. Therefore, another part of the data capture techniques based on Structure from Motion images is an algorithm well known by the scientific and academic community [37], which allows the construction of 3D models widely used in the field of motion structure archaeology and patrimonial architecture [38]. The photogrammetry workflow must manage a data plan based on measurement control points so that they are incorporated into Metashape’s Agisfof software [39] and, arriving at the intermediate process of postprocessing of the images, include the measurements that scale the final model. Control points are widely used for formal architectural control, in which an analytical model can be made after geometric analysis. Dos Santos et al. [40] revealed the complexity of the dimensional control of control points in the georeferencing of a record with a terrestrial laser scanner, through a scenario of interior and exterior spaces. In this complexity [41] carried out a study that examined the georeferencing and geometric quality of a record in SfM through multiple combinations of Ground Control Points (GCP). The authors´conclusions establish the proportionality of the control points in a uniformly distributed distribution. For this case, 15 control points were used using targets and natural control points, perfectly identified and distributed in two vertical planes, one distribution on the wall to which the altarpiece is attached and another vertical plane that constitutes the structure of the altarpiece itself. From the photogrammetric process, a dense cloud of points was obtained in Fig. 3, reaching 1.052.000 registered surface points. Control points were taken by the LEICA Flexline TS02 total station, with a precision of 2 mm [42]. A complete description of the photogrammetry processing methodology used is found in previous work [43,44] and well defined in the workflow [45]. The orientation of the base station was fixed by means of the local XYZ coordinates established at a single point of the project which were taken as 100, 100, and 10 m. Photogrammetry recording is performed using a NIKON D80 digital reflex camera, with a 12 MP sensor, with the following size: 23.6–15.6 mm, Nikon DX AF-S NIKKOR 18 to135 mm f/3.5– lens. 5.6 GE and a tripod. Focal length was 18 mm, optical image stabilizer, and exposure (fixed) 1/400 sf 3.5. The CCD sensor size was 23.6 mm ×15.8 mm, spread over 3872 ×2592 pixels for maximum resolution in NEF RAW format. The ISO value was set to 200. Once the image package was obtained, it was processed using Darktable software [46], improving the parameters. This software has the advantage of being open-source, allowing for improved photo development. Currently, a large number of scientific studies of SfM are focused on determining the distribution of GCP and the number in relation to the quality of the surface. But to provide a roadmap for future research on the quality of geometry capture and transformation in the BIM environment, it is necessary to compare the two sets of points TLS iG and SfM iG registered in the cultural asset. Through Cloud Compare’s automatic alignment of the two point clouds and their analysis using the ICP algorithm, we can determine the coverage parameters on the surface (CP). These coverage parameters will be analysed from the application of the Cloud Compare ICP algorithm according to Fig. 4. Once the deviation results have been determined, it can be concluded that the SfM iG data set is suitable to model parts with simple geometries, while the TLS iG data set is more appropriate to optimize the analysis of the profiles. 4. Organization of the structure of the BIM methodology The BIM methodology applied to the Martínez Monta˜ n´ es altarpiece integrates geospatial technologies to generate hybrid point clouds, optimized using algorithms such as ICP. The process includes semiautomatic segmentation in CloudCompare, parametric modelling in ArchiCAD with progressive LOD/LOK levels, and an innovative BFMP technique to reconstruct historical profiles with millimeter precision. Additionally, this methodology phase evaluates Mesh-to-BIM methods (Poisson, Meshlab) to integrate textured organic elements, overcoming interoperability limitations. Collaborative georeferencing using BIMCloud and 3DReshaper geometric analysis ensure fidelity to the original. This approach systematizes the documentation of complex heritage, combining digital technologies with historical and artistic rigor for conservation and study. 4.1. Fitting of the point cloud in the BIM platform To undertake a BIM project of this calibre and apply a methodology, a series of important steps must be performed in an HBIM project. First, a working group must be established among project operators through a collaborative project such as Teamwork. The church’s global point cloud (TSi) is exported to geo-reference the context where the altarpiece is Fig. 3. Detail of the dense cloud of points from the photogrammetry of the Altarpiece by Martínez Monta˜ n´ es. J. Moyano et al. Automation in Construction 175 (2025) 106213 5 located. Second, the modules of walls, pillars, and arches of the environment are structured to subsequently insert the photogrammetry point cloud and be geo-reference and located in the BIM environment, specifically as a partial point cloud (TSe). The essential part in the structure of the BIM teamwork project is the correct geopositioning of the building plot, provided by the electronic office of the Cadastre [47], entered into an ArchiCAD worksheet and inserted into a geo-referencing system. The structure must be adequately reconsidered through work levels, which for the case study are established coinciding with the cornice levels. It really is a process of rethinking before starting the modelling of the building’s structural systems both in its horizontal plane (x,y) and in its vertical plane (x,z). The layout of the levels of the element is adjusted to the levels of the church model, taking into account the level of the ground floor on which said furniture sits. The next step is to organise the altarpiece according to the segmentation of the main and secondary structural units. In this sense, it is done with the help of semantic segmentation through the CloudCompare software. The classification is done through the scalar field [48] taking different planes in which the surface of the pictorial paintings can serve as important reference elements (see previous Fig. 2 b). Once segmentation by level sectors is achieved, relative data are obtained, helping to assemble the structure. Subsequently, modelling begins with an LOD-100 for those basic elements, progressively increasing the levels of development until reaching the artisanal-level work in BIM. Similarly, the required Level of Information (LoK) is addressed, first through non-graphic characteristics, which are later included, until the knowledge LOK 400 is reached, covering the classification of damage, conservation, and prevention. 4.2. Teamwork development We know from previous work [27] that some platforms allow for the transmission of coordinated information between operators in the same project. These activities are developed using the previously mentioned TeamWork concept in ArchiCAD software [49]. The active interconnection of TeamWork begins by registering the operator team in BIMCloud, which will later have access to all information through a Virtual Private Network (VPN). Actually, TeamWork is a system for the exchange of information and interoperability of the BIM platform that was created by Graphisoft in 1997. The creation of an HBIM project specifically for retable structures has a research and knowledge procedure on how to approach the work. Once the point cloud is imported into the HBIM project, it is organized by levels to develop the modelling. It is crucial to obtain a global TLS ix point cloud to establish the context and environment of the construction on which the altarpiece will be installed Fig. 5. However, it is preferable to insert it in geopositioned at the project’s origin, segmented appropriately to facilitate operability in the management of a large amount of data (the global point cloud of the interior has reached 4.7 GB, 1.940.20 million points). (See Fig. 6.) The working method appllies to any other material asset of a monumental or artistic nature, which is why a generic methodology for a precise workflow is being developed. The import of the TLS ix causes a slowdown of the system. The point cloud with a resolution of 0.02 m results in a file size of 2 GBytes for operational purposes. For this, there is the possibility of decimating the point cloud, this means decreasing the density of points in space in a totally homogeneous way. We know that the equipment’s capture can reach the acquisition of more than one million points per second according to the specifications of the manufacturers of scanner products (TLS). To reduce the processing load of the software, some authors [50] propose to decimate the point cloud, which can be done through the scanner’s own processing software, such as Cyclone, Metashape in the case of photogrammetry, processing software of point clouds such as CloudCompare and complementary software linked to BIM platforms, in the case of Revit and Recap. Most methods decimate the point cloud to speed up the process of software in building replica applicability in BIM. But decimating the point cloud means losing configuration properties and quality in terms of its shape and attributes, so the operator must assess the limits of this processing. Other fields of development are the validation of the decimation of the set of points with optimal values, and providing representative images for the Mesh-to-BIM process [48]. Following the work on levels of the HBIM project, the altarpiece structures have the peculiarity of being engaged in a vertical plane, where height and width predominate. As there is no basic CAD planimetry, we have worked directly with the orthogonal plans provided by the point cloud and modeled directly with its reference within the BIM project. Yes, in the cases of analysis where orthophotos are obtained by means of photogrammetry, it would be very interesting to establish Fig. 4. a) Analysis of the difference between the TLS iG and the SfM iG . point cloud. Result of applying the C2C algorithm where the colour map shows the distance distribution, b) histogram of the analysis. Histogram units: metres (X axis) and number of points (Y axis). J. Moyano et al. Automation in Construction 175 (2025) 106213 6 worksheets with different orthogrammetric projections. This way of proceeding can detect metric discrepancies between massive data capture systems. Therefore, in this work, the discrepancies between the point cloud obtained by the SfM and the TLS in its three dimensions were also evaluated in Fig. 4. Next, a network system of axes linked to the project is obtained, and the altarpiece-architectural structure. Nieto et al. [27] mentioned the enormous advantages of these auxiliary systems that allow direct linkage with singular points of the project. From this, the units are built according to their material characteristics - type of structural wood - through profiles and decorative elements on the four developed levels. It is necessary to think that 3D reconstruction based on structure models can benefit from the grammar of forms originally introduced by Sting and Gips [51] for models of paintings sculptures and that were transferred to architecture and urbanism. A form grammar in principle defines the geometric-formal language, which is a set of finite-length sequences of symbols [52]. The altarpieces as architectural units can be divided and represented by a set of basic geometric forms, these forms are governed by Murphy et al. [24] by replacement rules in which a shape can be changed or replaced by transformations. The original idea of these authors is to model, through form grammar, the architectural languages of classical architecture, implemented using the construction of parametric objects. Fig. 5. Visualisation of the point cloud of the interior of the Church of the Annunciation. 1940.20 million points (Leica Truwiew). Fig. 6. Cornice contours processed using Cloud Compare. J. Moyano et al. Automation in Construction 175 (2025) 106213 7 4.3. Geometric characterisation of the profile units The identification of the geometric rules governing the different profiles that constitute the structure of an altarpiece model is necessary to interpret the structure’s final concept. The definition of the geometric shape of an element with historical and artistic interest through physical and digital models is a solid attempt for the specific analysis of volumetric, formal, constructive, and structural analysis aspects. The more complex the shape, the more crucial it is to reliably relate it to a correct geometric matrix [53], to allow the best interpretation of the evolution of the construction [54] and its adaptation to the real shape. Thus, one of the methodological processes described by Floriano et al. [53] involves the Best Fit Analysis (BFA where the processing aims to identify the most probable design shape of a dome by determining the underlying geometric rules. When building a structure composed of multiple profiles, it is a challenging to establish the geometric characterisation of each of the cornices for subsequent modelling. To address this, a workflow was developed based on a new methodology aimed at obtaining the best fit model profiles - Best Fit Model Profiles (BFMP). This model was developed after several software based experiments through the comparison and generation of profiles such as the 3DReshaper software [55], now know as Cyclone 3DR, through a modelling process based on the point cloud. The idea of using this new methodology emerged after learning about the potential of certain software applications used to evaluate linear tunnel trajectories for reporting purposes in civil engineering. Currently, the HBIM knowledge area questions two approaches that can be considered as basic hypotheses of a general nature; i) The first is whether we can build geometric components from surveys, without using the parametric object library; and ii) The second is to follow the logic of the operation of scan-to-BIM [56]. Scan-to-BIM makes it possible to generate a 3D model from the point cloud, for which there are semiautomatic procedures set out in the context of architectural heritage [57]; But the question that arises is whether the semi-automatic procedure reflects the true reality of the complex geometry of the patrimony or is it simply a simplification. To address this problem, this research proposes that each of the profiles cataloged in the altarpiece database be carried out using a Best Fit Model Profiles (BFMP) model. This procedure guarantees the reliability of the proposal of the parametric model. The basis of the work is the performing of a segmentation of each of the cornices with the help of the Cloud Compare software [58]. For this part of the campaign, the larger cornice of the entablature of the second body is taken (6). The geometric analysis procedure begins with the export of the SfM iX1 point cloud to 3DReshaper, and subsequently an analysis a polar contour analysis of the complete surface of the element is performed, to determine the variations that occur, and if these alterations of the surface recorded by the point cloud you can determine an optimal result Figure. To clarify the process of this phase, the cornice is taken Fig. 7, the part analysed in this case is a protruding body, since the cornice does not have a straight directrix along the entire width of the altarpiece’s entablature. An analysis of each of the straight fractions is carried out. Once the analysis of polar contours has been carried out, it is possible to determine from several sections perpendicular to the directrix of the cloud of points of the cornice in Fig. 8 a, the model that governs the geometric rules. The SfM iX1 set of points provides precise information about the geometry and also provides us with the variations of the rules established between the general profile model with and other figures that appear along the trajectory of the cornice and that must be taken into consideration. From the set of points determined in the 3DReshaper software, we derive a mesh surface that represents the model of the chosen cornice. The optimisation algorithm allows one surface to be moved over another in order to compare the distance between points that make up the different profiles Fig. 7. In the selection process, the operator selects the blue-tones range within the polar contour band, representing the lowest dispersion between the values. The optimized profile will be identified within this chosen band. The result of the comparison between the optimized profile and the real profile extracted from the point cloud indicates that the differences can range between 7 and 9 mm (green colour range), thus leading to the creation of the best fit profile model. Taking into account the USIBD [59] guide range the result would be around LOA 40–50. Through the 3D deviation colour map in Fig. 7, it is possible to visualize the outcome of the geometric Best Fit Model Profile (Figure b). The profile optimized through this procedure is exported in vector format (.dxf) to be inserted into the BIM model, as part of the modelling process. Conservators, architects, and engineers can use the implementation of a geometric process based on geodetic data obtained through the MCDSs and evaluate, through an analytical model, the nonarbitrary selection of a profile that in other cases could offer little reliability of a profile that in other cases could offer little guarantee. Once the analytical process of the geometric BFMP Fig. 9 has been resolved Fig. 7. Analysis of the polar contours of the cornice. The histogram shows the deviations along a mesh plane generated by same software. J. Moyano et al. Automation in Construction 175 (2025) 106213 8 with the variable surface elements perpendicular to the cornice directrix, the method can be extended to find other profiles that generate a change in the cornice trajectory. For example, Fig. 10 shows how the lines that join its nodes can determine a continuous ruled surface and where the deviation occurs through the extreme colours of its parts. A ruled surface satisfies eq. 1 that: r(u, v) φ c(u) +vw(u). Fig. 8. a) Identification of points extracted from profiles. b) Straight sections generated by vertical planes. Fig. 9. Deviation of the optimized profile and profile through the point cloud. The colour palette illustrates the range of deviations, while the brown surface represents the mesh generated by Cyclone 3DR. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Fig. 10. Deviation from the optimized profile and discontinuous profile. The colour palette illustrates the range of deviations. J. Moyano et al. Automation in Construction 175 (2025) 106213 9 Within the scope of the geometric characterisation of complex surfaces that constitute the structure of the altarpiece, profile evaluation enables effective analytical procedures. Thus, in this research, there is an analysis of the profile called the best-fit profile, which is actually an optimized profile. Certain scientific studies already show the importance of verifying the 3D models of the projects, so that the dimensions and shape are fixed in an exhaustive representation [88]. With this aim, an analytical comparison model was developed to contrast the best-fit profile with the original mesh generated from the point cloud. The data was obtained from a fragment of the cornice and processedusing the Cyclone 3DR software (Fig. 20). Based on the different profiles, measurements of the respective deviations between the mesh and the point cloud are obtained, thereby determining their corresponding change indicators. The analysis of cornice discontinuities is conducted using Cyclone 3DR tool [89] to compare the tunnel geometry. Although this procedure is developed for the analysis of deviation in closed geometries of civil engineering, through the study it has been possible to obtain a set of results of the Fig. 19. Editing scheme of the HBIM project. Definition of the “Damage Analysis” of the painted object. Fig. 20. Representation of the mesh difference between the best-fit model (blue colour) and the mesh generated from the set of cornice points (brown colour), analysis in Cyclone 3DR. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) J. Moyano et al. Automation in Construction 175 (2025) 106213 16 deviation between BFMP and each of the profiles generated by the software. The procedure begins by selecting a reference profile, from which a cross-section is created, followed by the generation of successive sections along the neutral axial axis that runs the full length of the cornice. The software itself develops a graph of the generation of the different profiles as shown in Fig. 21. In the scientific literature and as far as we have been able to investigate, only Koehi et al. [90] work on tunnel analysis, but in a very succinct way without reaching the deviation analysis of each one of the profiles and Gikas [91] to compare the precision between the TLS and a total station (ST) or, lastly, very recently, Xiang [92] who develops a comparison diagram model. In any case, it is the first document on the analysis of profiles in works of art, applying a point-based change estimation method. This study procedure leads us to determine a series of geometric characterisation of discontinuities of complex shapes in architecture such as the analysis of an altarpiece, which although it does not have the nature of the importance of the uncertainty that is generated in civil works, it is important to rigorously establish the precise geometry of an artistic work. The workflow of the connection between the different software and the applicability of the BIM software is shown in Fig. 22. (See Fig. 23.) Once the output data set is obtained, an analysis is carried out on each of the six profiles generated in order to evaluate the discontinuities present in the capture process between the optimized profile and and the remaining cross-sectionathe profiles of the cornice. A total of 58 measurements generated by Cyclone 3DR software have been developed. The limits of the spacing of points obtained and that define each one of the sections of the profile can take positive values if they are above the optimal curve or negative below the curve; therefore, the upper graph of Fig. 13 it includes values above 0.00 and below it. In the case of Profiler 2, the number of points generated has been lower in Profiles 4, 5, and 6. This number of points (37), which represents Profiler 2, marks a straight section of a mesh whose length is shorter than other profiles, see Fig. 20 in blue, and the satisfaction of the range of best profiles obtained using BFMP for the case study. of the altarpiece is determined in the box-andwhisker plot. In the lower part of the graph, the deviation values in each of the profiles are represented by means of box diagrams, with profiles 4 and 6 being the best fits and those that represent fewer deviations reaching standard deviation values of 0.00796 and 0.00944 m. In the table 1 outside graph the minimum, maximum, and median values of the results obtained can be determined. It should be noted that the simple absolute deviation (Dx) is in the value of 0.0125 m, according to eq. 4. The dispersion is represented in the graph by means of the simple absolute deviation between the mesh generated from the photogrammetry point cloud and the mesh generated from the optimal profile. The metric variations represented in Figure include the total width of the analysed cornice. The average variation was analysed along the artefact, as Moyano et al. [93]. The average value yielded errors (Δ Z ), and the simple absolute deviation (Dx) was calculated as per Eq. 4. Dx=∑ N i=1 |xi −x| N(4) where (Dx) is the simple absolute deviation, N is the sample size, x accounts for the observed values and x is the average value of the sample (in meters). On the other hand, the configuration of an architectural wall structure, which is structured in very characteristic parts and elements such as columns, shafts, capitals, lintels, pediments, and cornices, is addressed under an HBIM framework of parametric elements. Therefore, the construction of these structures is easily acceptable. On this consideration, a study framework is addressed where the process of the cloud of points to the BIM model, would go through a study to convert the different 3D sculptures that make up the altarpiece to mesh. However, integrating these detailed three-dimensional models into BIM environments necessitates the use of intermediate software platforms, as standard BIM tools often lack the capacity to natively handle complex textured meshes. Therefore, several data processing workflows must be carried out across different software environments to ensure that the final BIM model retains optimized texture quality, achieving a balance between processing efficiency and visual fidelity. Moreover, the resulting mesh models must be agile and fully operational within the chosen BIM system to support further applications such as documentation, conservation, or visualisation. In this regard, Rhinoceros software serves as the primary platform for processing and managing models that include pictorial or artistic textures, ensuring a reliable foundation for subsequent integration into the BIM workflow. Other considerations to be taken into account are those related to the semantic record of the elements cataloged in the HBIM altarpiece project. In this regard, the appropriate use of entities, as indicated in the Fig. 21. Create sections along the axis, using Cyclone 3DR software. J. Moyano et al. Automation in Construction 175 (2025) 106213 17 PlanBim guide [94], outlines twelve key points for the delivery of a BIM model. These twelve criteria of the classification system are an essential part of the regulations, where the code plays a vital role in the identification of objects. The Entity Information Matrix (EIM), designed to address the challenge of an orderly and well-structured classification, is crucial before starting the building information modelling, an original contribution in the field of altarpiece studies. The structure is formed from the segmentation of the structural units that make up an altarpiece or architectural façade The way to proceed in BIM to export the model, in Excel format, must be maintained from the beginning through diagrams on the same BIM platform. At the same time, the layered model can be preserved for use via worksheets within the BIM software itself. Therefore, all this information must be part of the HBIM project. This represents the initial step towards the implementation of the model in the heritage sciences sector, involving the organization of geometric Fig. 22. Workflow that explains the process from the segmentation of the cornice with the identification to a statistical step that shows the geometry of the segmentation of the cornice, then choosing the best profile adjustment model to achieve the optimal geometry to export it to the BIM environment. Fig. 23. Graph of the deviations of the six profiles analysed and absolute deviation. J. Moyano et al. Automation in Construction 175 (2025) 106213 18 elements prior to parametric modelling, where the relevant IFC standards are integrated into the final process. After reviewing recent work and analysing the contribution presented, the main limitation we encountered is the automation of complex elements in BIM. One of the major challenges in this work is transferring figures and artefacts with textures into these new platforms. This is based on the fact that, while qualitative interpretation of a scene comes naturally to humans, computers still face certain limitations, despite significant advances in computer engineering. These limitations are generally related to software [95]. Another important issue to resolve is the ability of BIM platforms to work directly with point clouds in a simultaneous manner. Currently, some companies, such as Solutions GmbH, have developed a point cloud manager for ArchiCAD and other platforms. This allows files to be imported without going through the . e57 format, and from a wide variety of both structured and unstructured files. 7. Conclusions The actions involved in the 3D digitisation of Cultural Heritage can be understood as a process of conversion and transformation through automation, particularly when applying analytical methodologies to data acquisition records. The modelling processes require work phases that integrate systematic processes that comprise the different stages, from analogue measurements to measurements based on sensors and laser emissions and modelling of historical information. Technological devices, as well as audiovisual content from users with entities of three-dimensional object entities, have put the industry on a development plane. The Industrial Revolution 4.0 which highlights the level of operational technology with the level of information technology is changing the way of understanding the industry and construction sector. Therefore, in this appropriate direction towards new models of digital transformation. An original work that is based on an innovative structure the analysis of the study of structures, of movable and immovable property. Different analysis methodologies are proposed through reverse engineering that allows the reconstruction of a model of construction model in a complex and difficult to interpret field such as Cultural Artistic Heritage. From photogrammetry, an experimental process was developed, focusing on the geometric analysis of the profiles that compose the structure of an altarpiece. The use of specific algorithms applied and based on a new methodology to achieve the Best Fit Model Profiles (BFMP) model was explored, reaching the point of establishing models close to measurements of units of millimetrers. Profile measurements can be used to infer shape knowledge and estimate the most efficient and accurate section from this proximity analysis for further construction. The upper cornice was used as a test bench, optimizing the model from the generation of different successive profiles. Although for future work, test benches will be adopted with greater difficulty in the shapes and complexity of the curvatures, in order to observe the behaviours through other parameters. The quality of the photogrammetry registration model was compared with the resultant extracted from the terrestrial laser scanner, which has made it possible to determine the estimated precision guarantee for the historical building information model. The organization of the data in a BIM project structure requires an efficient interoperability valid for all the collaborators involved. This link between operators can be developed through an ArchiCAD Teamwork project environment, where data is shared, refreshed, and approved, based on the BIMcloud framework. A robust platform for multidisciplinary collaboration in design and data transmission between architects, engineers, and restorers. The latest innovations focus on security and immediate data synchronisation, with an interconnection via Virtual Private Network (VPN). The base of a selection of round objects such as the sculpture in the centre of the altarpiece, for its insertion in the BIM platform, incorporates one of the most difficult tasks given the workflow that it entails between different software. For this work, several surveys were carried out on the basis of processing from the cloud of points of the altarpiece in which Jesus is baptised by Saint John. Currently, inserting a textured mesh into BIM platforms is more complicated than building the structure itself, since the mesh must contain the UV mapping image assigned to the digitised 3D model. In the future, it will be possible to study new ways and workflows that simplify the mesh using ‘Guadmesh in Rhino” and export this object to ArchiCAD image models. The choice of the case study justified the knowledge of the problem of a real artefact, segmented from the global point cloud to complement the altarpiece structure. One of the main scientific contributions of this work has been the creation of a classification structure according to the BIM classification system. When models are established that improve interoperability in this work, the Entity Information Matrix (EIM) is created, which is an information exchange and structure classification scheme. This process follows an analytic matrix model in which each structure can incorporate identifiable ID codes structured into classes, subclasses, and elements. Each and every one of the studies of facades, analysis of buildings, portals, courtyards containing architectural structures in the context of 3D scanning and historical information models of the building should in our opinion contain the Entity Information Matrix. This new model created on the basis of reflexions on architectural structures is the key to knowledge in the identification of elements in a later stage for the development and construction of the model. Attention to data quality, semantic classification, and interdisciplinary collaboration is crucial to ensure that models serve not only as accurate representations but also as effective tools for the conservation and management of cultural heritage. In the future, these implementation models should be explored for potential applications in other conservation domains, including diagnostics, material studies, and degradation assessments, among others. The focus here is on the use of Historic Building Information Modelling (HBIM) in the conservation of works of art. It is well established that the HBIM methodology is effective not only for cataloguing but also for the recovery and planning of conservation and restoration projects of architectural assets, while also establishing links between the approach and the methodologies employed. However, due to the complexity of the study, there is a future intention to apply the scalability of these methods to other types of movable cultural heritage or more complex architectural objects. CRediT authorship contribution statement Juan Moyano: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Resources, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Eva Martínez: Validation, Software. Juan E. Nieto-Juli´ an: Visualization, Supervision, Software, Formal analysis. María Fern´ andez-Alconchel: Supervision, Project administration, Funding acquisition. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This research was funded by the University of Seville through the VII Own Research and Transfer Plan (VII PPIT-US). The authors thank the Administration of the Universidad de Sevilla for providing access to the building. Thanks to the Administration of the SGI Fototeca-Laboratorio de Arte of the University of Seville. J. Moyano et al. Automation in Construction 175 (2025) 106213 19 Data availability No data was used for the research described in the article. References [1] M. Vecco, A definition of cultural heritage: from the tangible to the intangible, J. Cult. Herit. 11 (2010) 321–324, https://doi.org/10.1016/j.culher.2010.01.006. [2] S. Cursi, D. Simeone, I.A. Toldo, Semantic web approach for built heritage representation, in: International Conference on Computer-Aided Architectural Design Futures 527, Springer-Verlag, Berlin Heidelberg: Berlin, Heidelberg, 2015, pp. 383–401. [3] Zayed Tarek, Al-SakkafAbobakr, BagchiAshutosh a sustainability based framework for evaluating the heritage buildings, Int. J. Energy Optim. Eng. 9 (2020) 49–73, https://doi.org/10.4018/IJEOE.2020040105. [4] A. Osello, G. Lucibello, F. Morgagni, HBIM and virtual tools: a new chance to preserve architectural heritage, Build 8 (2018) 12, https://doi.org/10.3390/ BUILDINGS8010012. [5] A. Morales, Patrimonio hist´ orico artistico conservaci´ on de bienes culturales, 1996. [6] DigitalEurope Digital building transformations for Europe’s green renovations: Sustainable living and working, Available online, https://www.digitaleurope.org /resources/digital-building-transformations-for-europes-green-renovations-sustain able-living-and-working/, 2025. [7] C. Boje, A. Guerriero, S. Kubicki, Y. Rezgui, Towards a semantic construction digital twin: directions for future research, Autom. Constr. 114 (2020) 103179, https://doi.org/10.1016/J.AUTCON.2020.103179. [8] D. Hartmann, H. van der Auweraer, Digital Twins, in: SEMA SIMAI vol. 5, Springer Series; Springer Science and Business Media Deutschland GmbH, 2020, pp. 3–17. [9] N. Gim´ enez, J. Francisco, La conservaci´ on del Patrimonio Arquitect´ onico. Debates heredados del siglo XX, in: Noguera Gim´ enez, Juan Fr. La Conserv. del Patrim. Arquit. Debates heredados del siglo XX. En Ars longa Cuad. arte, 2002, No. 11 107–123, 2002. [10] G. Caroti, I. Martínez-Espejo Zaragoza, A. Piemonte, Range and image based modelling: a way for frescoed vault texturing optimization, ISPRS - Int. arch. Photogramm. Remote Sens. Spat. Inform. Sci. XL-5/W4 (2015) 285–290, https:// doi.org/10.5194/ISPRSARCHIVES-XL-5-W4-285-2015. [11] UNESCO Concepto de Patrimonio Digital, Available online, https://en.unesco. org/themes/information-preservation/digital-heritage/concept-digital-heritage, 2025. accessed on Jan 21, 2022. [12] D. Sandron, A. Tallon, Notre Dame Cathedral, Notre Dame Cathedr. (2020), https://doi.org/10.1515/9780271087726/HTML. [13] M. Bassier, S. Vincke, R. de Hernandez, M. Vergauwen, An overview of innovative heritage deliverables based on remote sensing techniques, Remote Sens. 10 (2018) 1607, https://doi.org/10.3390/RS10101607. [14] O. Cantos Martínez, J.M. Lodeiro P´ erez, F.J. Laguna Rodríguez, La fotogrametría como apoyo gr´ afico en la restauraci´ on de retablos escult´ oricos en madera policromada, Patrim. Cult. Espa˜ na (2009) 237–251. ISSN 1889–3104, No. 1, 2009, p´ ags. 237–251. [15] M. D´ avila, Restituci´ on fotogram´ etrica de retablos. Naves laterales de la Iglesia de San Jacinto, Caracas, Blucher Des. Proc. (2014) 158–161, https://doi.org/ 10.5151/DESPRO-SIGRADI2014-0028. [16] K. Hanke, M. Moser, R. Rampold, K. Hanke, M. Moser, R. Rampold, Historic photos and TLS data fusion for the 3D reconstruction of a monastery altar ensemble, ISPAr XL5 (2015) 201–206, https://doi.org/10.5194/ISPRSARCHIVES-XL-5-W7-2012015. [17] R. Argiolas, A. Cazzani, E. Reccia, V. Bagnolo, From lidar data towards HBIM for structural evaluation, Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. - ISPRS Arch. 42 (2021) 125–132, https://doi.org/10.5194/ISPRS-ARCHIVES-XLII-2-W15125-2019. [18] E. Abbate, S. Invernizzi, A. Span` o, HBIM parametric modelling from clouds to perform structural analyses based on finite elements: a case study on a parabolic concrete vault, Appl. Geomat. (2020) 1–18, https://doi.org/10.1007/S12518-02000341-4/FIGURES/17. [19] G. Rocha, L. Mateus, J. Fern´ andez, V. Ferreira, A scan-to-BIM methodology applied to heritage buildings, Herit 3 (2020) 47–67, https://doi.org/10.3390/ HERITAGE3010004. [20] M. Bassier, G. Hadjidemetriou, M. Vergauwen, Implementation of scan-to-BIM and FEM for the documentation and analysis of heritage timber roof structures, Digit. Herit. Prog. Cult. Herit. Doc. Preserv. Prot. 1 (2016) 79–90, https://doi.org/ 10.1007/978-3-319-48496-9. [21] F. Bosch´ e, M. Ahmed, Y. Turkan, C.T. Haas, R. Haas, The value of integrating scanto-BIM and scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: the case of cylindrical MEP components, Autom. Constr. 49 (2015) 201–213, https://doi.org/10.1016/j.autcon.2014.05.014. [22] N. Hidaka, T. Michikawa, A. Motamedi, N. Yabuki, T. Fukuda, Polygonization of point clouds of repetitive components in civil infrastructure based on geometric similarities, Autom. Constr. 86 (2018) 99–117, https://doi.org/10.1016/J. AUTCON.2017.10.014. [23] M. Andriasyan, J. Moyano, J.E. Nieto-Juli´ an, D. Ant´ on, From point cloud data to building information modelling: an automatic parametric workflow for heritage, Remote Sens. 12 (2020) 1094, https://doi.org/10.3390/RS12071094. [24] M. Murphy, E. McGovern, S. Pavia, Historic building information modelling - adding intelligence to laser and image based surveys of European classical architecture, ISPRS J. Photogramm. Remote Sens. 76 (2013) 89–102, https://doi. org/10.1016/j.isprsjprs.2012.11.006. [25] D. Oreni, R. Brumana, A. Georgopoulos, B. Cuca, HBIM library objects for conservation and management of built heritage, Int. J. Herit. Digit. Era 3 (2014) 321–334, https://doi.org/10.1260/2047-4970.3.2.321. [26] J. García-Le´ on, P. S´ anchez-Allegue, C. Pe˜ na-Velasco, L. Cipriani, F. Fantini, Interactive dissemination of the 3D model of a baroque altarpiece: a pipeline from digital survey to game engines, SCIRES-IT - Sci. Res. Inf. Technol. 8 (2019) 59–76, https://doi.org/10.2423/I22394303V8N2P59. [27] J.E. Nieto-Juli´ an, L. Lara, J. Moyano, Implementation of a TeamWork-HBIM for the management and sustainability of architectural heritage, Sustainability 13 (2021) 2161, https://doi.org/10.3390/su13042161. [28] C. Bonet Blanco, El retablo barroco, escenografía e imagen, in: Proceedings of the El Monasterio del Escorial y la pintura (Actas del Simposium); Sevilla, ed. F.J.C. y F. de, Ed.; San Lorenzo de El Escorial: Real Colegio M a Cristina, 2001, pp. 623–642. [29] G. Borruso, W. Huang, G. Balletto, W. Kainz, N. Abreu, A. Pinto, A. Matos, M. Pires, Procedural point cloud modelling in scan-to-BIM and scan-vs-BIM applications: a review, ISPRS Int. J. Geo-Information 12 (2023) 260, https://doi.org/10.3390/ IJGI12070260. [30] J. Lafita Díaz, Conferencia sobre el retablo de San Juan el Bautista de la iglesia conventual de Nuestra Se˜ nora del Socorro, in: Boletín Bellas Artes, ISSN 0210–6531, No. 4, 1939 (Ejemplar Dedic. a Homen. a Martínez Monta˜ n´ es (1568–1649)), 1939, pp. 139–150. [31] L.M. Lara, Juan Martínez Monta˜ n´ es, autor de la traza del primitivo retablo de Francisco de Rioja en el convento de Las Teresas de Sevilla, Lab. ARTE 21 (2008) 395–409, https://doi.org/10.12795/LA.2008.I21.21. [32] Hern´ andez Díaz, J. Estudio iconogr´ afico y t´ ecnico de la imaginería monta˜ nesina. Boletín Bellas Artes, ISSN 0210–6531, No. 4, 1939 (Ejemplar Dedic. a Homen. a Martínez Monta˜ n´ es (1568–1649)), p´ ags. 54–104 1939. [33] I.A. de Cultura, de Proyecto de conservaci´ on “retablo de San Juan Bautista” (1610–1620-1622); Sevilla, 2020. [34] S. Bertacchi, G. Bertacchi, L. Cipriani, Chiuro laboratory: integration of workflows from digital survey to optimised 3D urban models for interactive exploration, Appl. Geomat. (2021) 1–20, https://doi.org/10.1007/S12518-020-00352-1/FIGURES/ 13. [35] E.L.A. Bordini, Le robbiane al Santuario della Verna : sperimentazioni di rilievo digitale e modellazione 3D =The robbiane at the Sanctuary of La Verna : digital survey and 3D modeling experiences. Le robbiane al St. della Verna Sper. di rilievo Digit. e Model. 3D =robbiane Sanctuary La Verna Digit. Surv. 3D Model. Exp, 2019, pp. 761–768, https://doi.org/10.36165/1184. [36] J. Moyano, ´ A. Justo-Estebaranz, J.E. Nieto-Juli´ an, A.O. Barrera, M. Fern´ andezAlconchel, Evaluation of records using terrestrial laser scanner in architectural heritage for information modeling in HBIM construction: the case study of the La Anunciaci´ on church (Seville), J. Build. Eng. 62 (2022) 105190, https://doi.org/ 10.1016/J.JOBE.2022.105190. [37] H. Park, D. Lee, Comparison between point cloud and mesh models using images from an unmanned aerial vehicle, Measurement 138 (2019) 461–466, https://doi. org/10.1016/J.MEASUREMENT.2019.02.023. [38] M. Borrero, L.R. Stroth, A proposal for the standardized reporting of error and Paradata regarding structure from motion (SfM) 3D models used in recording and consolidating archaeological architecture, Adv. Archaeol. Pract. 8 (2020) 376–388, https://doi.org/10.1017/AAP.2020.11. [39] Agisoft PhotoScan software, Agisoft Metashape, Available online: https://www. agisoft.com/. accessed on Jan 30, 2020. [40] D.R. dos Santos, A.P. Dal Poz, K. Khoshelham, Indirect Georeferencing of terrestrial laser scanning data using control lines, Photogramm. Rec. 28 (2013) 276–292, https://doi.org/10.1111/phor.12027. [41] E. Sanz-Ablanedo, J.H. Chandler, J.R. Rodríguez-P´ erez, C. Ord´ o˜ nez, Accuracy of Unmanned Aerial Vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used, Remote Sens. 10 (2018) 1606, https://doi.org/10.3390/RS10101606. [42] Geosystems Leica Geosystems, Leica FlexLine TS02/TS06/TS09 user manual, Available online: https://leica-geosystems.com/, 2008. accessed on Mar 16, 2020. [43] J. Moyano, J.E. Nieto-Juli´ an, D. Ant´ on, E. Cabrera, D. Bienvenido-Huertas, N. S´ anchez, Suitability study of structure-from-motion for the digitisation of architectural (heritage) spaces to apply divergent photograph collection, Symmetry (Basel). 12 (2020) 1981, https://doi.org/10.3390/sym12121981. [44] J. Moyano, M. Fern´ andez-Alconchel, J.E. Nieto-Juli´ an, M.J. Carretero-Ayuso, Methodologies to determine geometrical similarity patterns as experimental models for shapes in architectural heritage, Symmetry 14 (2022) 1893, https://doi. org/10.3390/SYM14091893. [45] M. Jaud, S. Passot, P. Allemand, N. Le Dantec, P. Grandjean, C. Delacourt, Suggestions to limit geometric distortions in the reconstruction of linear coastal landforms by SfM photogrammetry with PhotoScan® and MicMac® for UAV surveys with restricted GCPs pattern, Drones 3 (2018) 2, https://doi.org/10.3390/ drones3010002. [46] P. David, H. Darktable, Available online: https://www.darktable.org/, 2025. accessed on Jan 30, 2020. [47] Ministerio de Hacienda y Funci´ on Pública Sede Electr´ onica del Catastro - Inicio, Available online, https://www.sedecatastro.gob.es/, 2025. accessed on Jan 2, 2024. [48] J. Moyano, J. Le´ on, J.E. Nieto-Juli´ an, S. Bruno, Semantic interpretation of architectural and archaeological geometries: point cloud segmentation for HBIM parameterisation, Autom. Constr. 130 (2021) 103856, https://doi.org/10.1016/J. AUTCON.2021.103856. J. Moyano et al. Automation in Construction 175 (2025) 106213 20 [49] Grafisoft ArchiCAD, Available online, https://www.graphisoft.com/archicad/, 2019. accessed on Aug 6, 2019. [50] L. Sanhudo, N.M.M. Ramos, J.P. Martins, R.M.S.F. Almeida, E. Barreira, M. L. Sim˜ oes, V. Cardoso, A framework for in-situ geometric data acquisition using laser scanning for BIM modelling, J. Build. Eng. 28 (2020) 101073, https://doi. org/10.1016/J.JOBE.2019.101073. [51] G. Stiny, J. Gips, Shape grammars and the generative specification of painting and sculpture, in: Proceedings of the Information Processing 71, 1972. [52] S. Becker, Generation and application of rules for quality dependent façade reconstruction, ISPRS J. Photogramm. Remote Sens. 64 (2009) 640–653, https:// doi.org/10.1016/J.ISPRSJPRS.2009.06.002. [53] L. Floriano, M. Liuzzo, G. Margani, Geometric characterization of late-baroque domes in Sicily, Nexus Network Journal 24 (2022) 423–443, https://doi.org/ 10.1007/S00004-022-00594-Z/FIGURES/13. [54] R. Spallone, M. Vitali, Complex vaulted systems: geometry and architecture from design to construction, Nexus Network Journal 22 (2020) 799–809, https://doi. org/10.1007/S00004-020-00537-6/METRICS. [55] Hexagon, Leica Geosystems 3DReshaper Point Cloud Processing Sotware, Available online, https://leica-geosystems.com/es-es/products/laser-scanners/software/3dr eshaper. accessed on Mar 27, 2023. [56] M. Capone, E. Lanzara, Scan-to-BIM vs 3D ideal model HBIM: parametric tools to study domes geometry, ISPRS Ann. Photogramm. Remote Sens. Spat. Inform. Sci. 42 (2019) 219–226. [57] J. Moyano, J.E. Nieto-Juli´ an, L.M. Lenin, S. Bruno, Operability of point cloud data in an architectural heritage information model, Int. J. Archit. Herit. (2021) 1–20, https://doi.org/10.1080/15583058.2021.1900951. [58] D. Girardeau-Montaut, Cloud-to-Mesh Distance, Available online, http://www.clo udcompare.org/doc/wiki/index.php?title=Cloud-to-Mesh_Distance. [59] U.S. Institute of BUILDING Documentation USIBD Level of Accuracy (LOA) Specification Guide Document C120 TM [Guide] Version 2.0–2016 Guide for USIBD Document C220 TM : Level of Accuracy (LOA) Specification for Building Documentation, Available online: https://cdn.ymaws.com/www.nysapls.org/reso urce/resmgr/2019_conference/handouts/hale-g_bim_loa_guide_c120_v2.pdf, 2025. [60] L. Michel, X. Brunetaud, M. Mukhtar, B. Coignard, Digital sculptures rebuilt for computation, in: Proc. Digit. 2013 - Fed. 19th Int’l VSMM, 10th Eurographics GCH, 2nd UNESCO Mem. World Conf. Plus Spec. Sess. fromCAA, Arqueol. 2.0 al 2, 2013, p. 453, https://doi.org/10.1109/DIGITALHERITAGE.2013.6744808. [61] J. Hayes, S. Fai, S. Kretz, C. Ouimet, P. White, Digitally-assisted stone carving of a relief sculpture for the parliament buildings National Historic Site of Canada, ISPAn II5 (2015) 97–103, https://doi.org/10.5194/ISPRSANNALS-II-5-W3-972015. [62] J. Moyano, E. Cabrera-Revuelta, J.E. Nieto-Juli´ an, M. Fern´ andez-Alconchel, P. Fern´ andez-Valderrama, Evaluation of geometric data registration of small objects from non-invasive techniques: applicability to the HBIM field, Sensors 23 (2023) 1730, https://doi.org/10.3390/S23031730. [63] G. Keenaghan, E. Meegan, S. Scandurra, A. Corns, A. Chenaux, A. Sanseverino, B. Messina, M. Limongiello, C.G. Guida, An HBIM methodology for the accurate and georeferenced reconstruction of urban contexts surveyed by UAV: The case of the castle of Charles V, Remote Sens. 14 (2022) 3688, https://doi.org/10.3390/ RS14153688. [64] X. Yang, M. Koehl, P. Grussenmeyer, Mesh-to-bim: from segmented mesh elements to bim model with limited parameters, Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. - ISPRS Arch. 42 (2018) 1213–1218, https://doi.org/10.5194/isprsarchives-XLII-2-1213-2018. [65] M. Intignano, S.A. Biancardo, C. Oreto, N. Viscione, R. Veropalumbo, F. Russo, G. Ausiello, G. Dell’acqua, A scan-to-BIM methodology applied to stone pavements in archaeological sites, Herit 4 (2021) 3032–3049, https://doi.org/10.3390/ HERITAGE4040169. [66] R. Machete, A.P. Falc˜ ao, A.B. Gonçalves, M. Godinho, R. Bento, Development of a Manueline style object library for heritage BIM, Int. J. Archit. Herit. (2020), https://doi.org/10.1080/15583058.2020.1740825. [67] Robert McNeel & Associates Grasshopper Grasshopper, Available online, http s://www.grasshopper3d.com/, 2025. accessed on Mar 4, 2020. [68] V. Croce, G. Caroti, A. Piemonte, L. De Luca, P. V´ eron, H-BIM and artificial intelligence: classification of architectural heritage for semi-automatic scan-to-BIM reconstruction, Sensors 23 (2023) 2497, https://doi.org/10.3390/S23052497. [69] G. Colia, Structural Health Monitoring (SHM), Heritage building information modelling (HBIM) and remote sensing for existing bridge, 2021. [70] K. Themistocleous, A. Agapiou, D. Hadjimitsis, K. Themistocleous, A. Agapiou, D. Hadjimitsis, 3D documentation and BIM modeling of cultural heritage structures using UAVs: the case of the Foinikaria church, ISPAr 62W2 (2016) 45–49, https:// doi.org/10.5194/ISPRS-ARCHIVES-XLII-2-W2-45-2016. [71] M. Kazhdan, M. Bolitho, H. Hoppe, Poisson surface reconstruction, in: Proceedings of the Eurographics Symposium on Geometry Processing, 2006, pp. 1–10. [72] M. G´ omez Mora, R. Rodríguez Rodríguez, Modelado tridimensional de objetos heterog´ eneos a partir de im´ agenes m´ edicas: Herramientas y algoritmos, in: FABBECOR.ONG (Ed.), Proceedings of the Congreso Internacional M´ exicoColombia CICOM 2018 MEMORIAS Octubre 11, 2018, pp. 67–72 (ISSN: 24629588). [73] Cignoni, P.; Callieri, M.; Corsini, M.; Dellepiane, M.; Ganovelli, F.; Ranzuglia, G. MeshLab: an open-source mesh processing tool. In Proceedings of the In Eurographics Italian Chapter Conference; Scarano, V., De Chiara, R., Erra, U., Eds.; The Eurographics Association: Salerno, Italy, 2008. chrome-extension:// efaidnbmnnnibpcajpcglclefindmkaj/https://diglib.eg.org/server/api/core/ bitstreams/eb20f1e6-5138-42bf-8b32-f4326a619969/content. [74] J. Morel, A. Bac, C. V´ ega, Surface reconstruction of incomplete datasets: a novel Poisson surface approach based on CSRBF, Comput. Graph. 74 (2018) 44–55, https://doi.org/10.1016/J.CAG.2018.05.004. [75] Belnder Benchmark Software Blender, Available online, https://www.blender.org/ download/, 2025. accessed on Apr 5, 2023. [76] D. Di Donato, R. Morganti, A. Tosone, M. Abita, Procedural modelling for Hbim of Italian railways Iron bridges, ISPAr 46W1 (2022) 207–214, https://doi.org/ 10.5194/ISPRS-ARCHIVES-XLVI-2-W1-2022-207-2022. [77] E.S. Malinverni, F. Mariano, F. Di Stefano, L. Petetta, F. Onori, Modelling in hbim to document materials decay by a thematic mapping to manage the cultural heritage: the case of “chiesa della piet` a” in fermo. In proceedings of the ISPRS annals of the photogrammetry, Remote Sensing and Spatial Information Sciences; Copernicus GmbH 42 (2019) 777–784, https://doi.org/10.5194/isprs-archivesXLII-2-W11-777-2019. [78] BuildingSMART Spain Guía de Sistemas de Clasificaci´ on cuando se utiliza BIM, Available online: https://www.buildingsmart.es/recursos/clasificaci´ on-en-los-mo delos, 2025. [79] J. Moyano, E. Carre˜ no, J.E. Nieto-Juli´ an, I. Gil-Ariz´ on, S. Bruno, Systematic approach to generate historical building information modelling (HBIM) in architectural restoration project, Autom. Constr. 143 (2022) 104551, https://doi. org/10.1016/J.AUTCON.2022.104551. [80] EspacioBIM GuBIMClass, ¿qu´ e es GuBIMClass? | Espacio BIM, Available online, https://www.espaciobim.com/gubimclass. accessed on Apr 8, 2021. [81] O.C. System, OmniClass® - Construction Specifications Institute, Available online: https://www.csiresources.org/standards/omniclass. accessed on Apr 8, 2021. [82] J. Moyano, A. Musicco, J.E. Nieto-Juli´ an, J.P. Domínguez-Morales, Geometric characterization and segmentation of historic buildings using classification algorithms and convolutional networks in HBIM, Autom. Constr. 167 (2024) 105728, https://doi.org/10.1016/J.AUTCON.2024.105728. [83] G. Sammartano, M. Previtali, F. Banfi, Parametric generation in Hbim workflows for slam-based data: discussing expectations on suitability and accuracy, in: Proceedings of the Proceedings of the joint international event 9th ARQUEOL´ OGICA 2.0 & 3rd GEORES, 2021, pp. 374–388, https://doi.org/ 10.4995/arqueologica9.2021.12155. [84] S. Rusinkiewicz, M. Levoy, Efficient variants of the ICP algorithm, in: Proc. Int. Conf. 3-D Digit. Imaging Model. 3DIM, 2001, pp. 145–152, https://doi.org/ 10.1109/IM.2001.924423. [85] U. Stilla, Y. Xu, Change detection of urban objects using 3D point clouds: a review, ISPRS J. Photogramm. Remote Sens. 197 (2023) 228–255, https://doi.org/ 10.1016/J.ISPRSJPRS.2023.01.010. [86] T. Czerniawski, J.W. Ma, Fernanda Leite automated building change detection with amodal completion of point clouds, Autom. Constr. 124 (2021) 103568, https:// doi.org/10.1016/J.AUTCON.2021.103568. [87] M. Heidari Mozaffar, M. Varshosaz, Optimal placement of a terrestrial laser scanner with an emphasis on reducing occlusions, Photogramm. Rec. 31 (2016) 374–393, https://doi.org/10.1111/PHOR.12162. [88] H. Sofia, E. Anas, O. Faiz, Mobile mapping, machine learning and digital twin for road infrastructure monitoring and maintenance: Case study of mohammed VI bridge in Morocco, in: Proc. - 2020 IEEE Int. Conf. Moroccan Geomatics, MORGEO 2020, 2020, https://doi.org/10.1109/MORGEO49228.2020.9121882. [89] Geosystems, L, Leica Cyclone REGISTER 360-3D Laser Scanning Point Cloud Registration Software, Available online, https://leica-geosystems.com/products/la ser-scanners/software/leica-cyclone/leica-cyclone-register-360. accessed on Jan 24, 2021. [90] M. Koehl, D. Schueller, O. Barrot, S. Guillemin, M. Koehl, D. Schueller, O. Barrot, S. Guillemin, D modelling of tram tunnel from Tls point clouds for technical documentation and extraction of characteristic lines, ISPAr 43B2 (2022) 1047–1054, https://doi.org/10.5194/ISPRS-ARCHIVES-XLIII-B2-2022-1047-2022. [91] V. Gikas, Three-dimensional laser scanning for geometry documentation and construction management of highway tunnels during excavation, Sensors 12 (2012) 11249–11270, https://doi.org/10.3390/S120811249. [92] J. Xiang, Research on deformation monitoring of tunnel engineering based on 3D laser scanning, Appl. Math. Nonlinear Sci. (2022), https://doi.org/10.2478/ AMNS.2021.2.00204. [93] J. Moyano, C.P. Odriozola, J.E. Nieto-Juli´ an, J.M. Vargas, J.A. Barrera, J. Le´ on, Bringing BIM to archaeological heritage: interdisciplinary method/strategy and accuracy applied to a megalithic monument of the copper age, J. Cult. Herit. (2020), https://doi.org/10.1016/j.culher.2020.03.010. [94] PlanBim de CORFO Est´ andar BIM para Proyectos Públicos, Intercambio de informaci´ on entre solicitante y proveedores, Available online: https://planbim. cl/download/estandar-bim-para-proyectos-publicos/. accessed on Apr 14, 2023. [95] U. Hirschberg, A. Streilein, CAAD meets digital photogrammetry: modelling “weak forms” for computer measurement, Autom. Constr. 5 (1996) 171–183, https://doi. org/10.1016/0926-5805(96)00144-6. J. Moyano et al. Automation in Construction 175 (2025) 106213 21