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Thanks to its capability of archiving and organizing all the information about a building, HBIM (Historical Building Information Modeling) is considered a promising resource for planned conservation of historical assets. However, its usage remains limited and scarcely adopted by the subjects in charge of conservation, mainly because of its rather complex 3D modeling requirements and a lack of shared regulatory references and guidelines as far as semantic data are concerned. In this study, we developed an HBIM methodology to support documentation, management, and planned conservation of historic buildings, with particular focus on non-geometric information: organized and coordinated storage and management of historical data, easy analysis and query, time management, flexibility, user-friendliness, and information sharing. The system is based on a standalone specific-designed database linked to the 3D model of the asset, built with BIM software, and it is highly adaptable to different assets. The database is accessible both with a developed desktop application, which acts as a plug-in for the BIM software, and through a web interface, implemented to ensure data sharing and easy usability by skilled and unskilled users. The paper describes in detail the implemented system, passing by semantic breaking down of the building, database design, as well as system architecture and capabilities. Two case studies, the Cathedral of Parma and Ducal Palace of Mantua (Italy), are then presented to show the results of the system’s application.

This paper presents a comprehensive review of research on Historic Building Information Modeling (HBIM), focusing on its role as a tool for managing knowledge and supporting conservation practices of Architectural Heritage. While previous review articles and most research works have predominantly addressed geometric modeling—given its significant challenges in the context of historic buildings—this study places greater emphasis on the integration of non-geometric data within the BIM environment. A systematic search was conducted in the Scopus database to extract the 451 relevant publications analyzed in this review, covering the period from 2008 to mid-2024. A bibliometric analysis was first performed to identify trends in publication types, geographic distribution, research focuses, and software usage. The main body of the review then explores three core themes in the development of the information system: the definition of model entities, both semantic and geometric; the data enrichment phase, incorporating historical, diagnostic, monitoring and conservation-related information; and finally, data use and sharing, including on-site applications and interoperability. For each topic, the review highlights and discusses the principal approaches documented in the literature, critically evaluating the advantages and limitations of different information management methods with respect to the distinctive features of the building under analysis and the specific objectives of the information model.

Many unmanned aerial vehicles (UAV) host rolling shutter (RS) cameras, i.e., cameras where image rows are exposed at slightly different times. As the camera moves in the meantime, this causes inconsistencies in homologous ray intersections in the bundle adjustment, so correction models have been proposed to deal with the problem. This paper presents a series of test flights and simulations performed with different UAV platforms at varying speeds over terrain of various morphologies with the objective of investigating and possibly optimising how RS correction models perform under different conditions, in particular as far as block control is concerned. To this aim, three RS correction models have been applied in various combinations, decreasing the number of fixed ground control points (GCP) or exploiting GNSS-determined camera stations. From the experimental tests as well as from the simulations, four conclusions can be drawn: (a) RS affects primarily horizontal coordinates and varies notably from platform to platform; (b) if the ground control is dense enough, all correction models lead practically to the same mean error on checkpoints; however, some models may cause large errors in elevation if too few GCP are used; (c) in most cases, a specific correction model is not necessary since the affine deformation caused by RS can be adequately modelled by just applying the extended Fraser camera calibration model; (d) using GNSS-assisted block orientation, the number of necessary GCP is strongly reduced.

This study compares the photogrammetric performance of three multi-camera systems—two spherical cameras (INSTA 360 Pro2 and MG1) and one multi-camera rig (ANT3D)—to evaluate their accuracy and precision in confined environments. These systems are particularly suited for indoor surveys, such as narrow spaces, where traditional methods face limitations. The instruments were tested for the survey of a narrow spiral staircase within Milan Cathedral and the results were analyzed based on different processing strategies, including different relative constraints between sensors, various calibration sets for distortion parameters, interior orientation (IO), and relative orientation (RO), as well as two different ground control solutions. This study also included a repeatability test. The findings showed that, with appropriate ground control, all systems achieved the target accuracy of 1 cm. In partially unconstrained scenarios, the drift errors ranged between 5 and 10 cm. Performance varied depending on the processing pipelines; however, the results suggest that imposing a multi-camera constraint between sensors and estimating both IO and RO parameters during the Bundle Block Adjustment yields the best outcomes. In less stable environments, it might be preferable to pre-calibrate and fix the IO parameters.

This paper presents a low-cost framework for creating urban digital twins in Virtual Reality (VR) tailored for heritage preservation and smart city applications. The increasing demand for urban digital twins necessitates an integration of diverse data sources to enhance urban management, particularly in historical contexts where traditional methods may lack necessary specificity. To address this, our research integrates advanced 3D survey techniques (mostly low-cost) with publicly available datasets to develop a semantically rich, detailed urban digital model aligned with specific requirements of each unique urban setting.The methodology hinges on three pivotal stages: data acquisition, data management, and data accessibility. Data acquisition involves collecting extensive data both from existing datasets and 3D surveys, emphasizing on identifying optimal, cost-effective solutions suited to the surveyed area. Data management is achieved using a broker database coupled with a Web Application Programming Interface (Web API), ensuring the integrity of original databases while enabling flexible system implementation. Data accessibility extends to a broad range of applications, including GIS, BIM, and customized applications, enhancing the scalability of the digital twin model.The test ground of this system is a VR application developed with Unity, which serves as the interactive platform for the digital twin model. The proposed framework is validated through three case studies in distinct urban settings, each chosen to illustrate the framework's adaptability, versatility, and effectiveness in different urban complexities. The results demonstrate the potential of the digital twin model in facilitating detailed urban management tasks, promoting sustainable heritage conservation, and fostering smarter urban environments.

Digital surface models (DSM) have become one of the main sources of geometrical information for a broad range of applications. Image-based systems typically rely on passive sensors which can represent a strong limitation in several survey activities (e.g., night-time monitoring, underground survey and night surveillance). However, recent progresses in sensor technology allow very high sensitivity which drastically improves low-light image quality by applying innovative noise reduction techniques. This work focuses on the performances of night-time photogrammetric systems devoted to the monitoring of rock slopes. The study investigates the application of different camera settings and their reliability to produce accurate DSM. A total of 672 stereo-pairs acquired with high-sensitivity cameras (Nikon D800 and D810) at three different testing sites were considered. The dataset includes different camera configurations (ISO speed, shutter speed, aperture and image under-/over-exposure). The use of image quality assessment (IQA) methods to evaluate the quality of the images prior to the 3D reconstruction is investigated. The results show that modern high-sensitivity cameras allow the reconstruction of accurate DSM in an extreme low-light environment and, exploiting the correct camera setup, achieving comparable results to daylight acquisitions. This makes imaging sensors extremely versatile for monitoring applications at generally low costs.

This study presents low-cost techniques for monitoring soil erosion on mountain trails within the context of the HUMANITA project, which focuses on mitigating the environmental impacts from recreational activities in protected areas. Monitoring erosion in mountain environments poses several challenges that must be considered to select optimal techniques, such as limited accessibility, instrument portability, achievable level of detail, absence of data connectivity and Ground Control Point establishment. In addition, soil erosion is a widespread issue that requires surveys over large areas and must be repeated periodically to ensure accurate assessment and track changes over time. Consequently, the cost and ease of use of surveying equipment are critical.Six protected areas in Italy and Central Europe were selected as pilot sites. Three scenarios were explored, each characterized by different spatial extents and level of details required for erosion assessment: detailed analysis of small areas (scenario 1), narrow forest trails (scenario 2), and broad open areas (scenario 3). Scenario 1 employed high-precision techniques such as Terrestrial Laser Scanning and close-range photogrammetry to capture micro-scale changes. Scenario 2 utilized spherical photogrammetry and UAVs to survey narrow, vegetated trails with high resolution and accuracy. Scenario 3 focused on UAV photogrammetry for monitoring large areas. Key challenges included multi-epoch data co-registration, establishing stable ground control points, and ensuring and assessing surveys repeatability. The results highlight the capabilities, limitations, and cost-effectiveness of these geomatics techniques, providing practical guidelines for sustainable trail management and erosion monitoring in protected mountain areas.

Digital photogrammetry is a widespread surveying technique in different fields of application due to its flexibility, versatility and cost-effectiveness. Despite its increasing automation and simplicity, a proper image block design is crucial to ensure high standards of performance and accuracy. Studies on camera network design have been largely dealt with in the scientific literature with reference to image orientation process, while they are still poor on dense matching. This paper investigates the influence of different block geometry configurations on multi-image dense matching. Starting from the same orientation solution, dense matching was performed considering different combinations of number of images and base length distance between the first and the last image within a strip. The raster Digital Elevation Models (DEM) resulting from each sequence of images were compared with a reference DEM to assess accuracy and completeness. The tests were conducted using different cameras and at various test sites to assess different survey conditions and generalize the findings. The presented results provide some operational guidance on block geometry optimization to maximize the accuracy and completeness.

This paper investigates rapid survey methodologies for urban environments to support the compilation of the Italian Carta del Rischio del Patrimonio Culturale (Risk Map of Cultural Heritage, GIS developed by the Italian Ministry of Culture), with a focus on the documentation and assessment of Building Fronts in historic centres. The study addresses the need for acquisition strategies that balance accuracy requirements with constraints related to survey time and costs, while ensuring flexibility and long-term updatability. The proposed workflow was tested on a complete urban block in the historic centre of Mirandola (Modena, Italy), characterised by dense urban morphology, narrow streets, and ongoing post-seismic reconstruction. Data acquisition was based on spherical photogrammetry as the primary rapid survey technique, complemented by Google Street View panoramas to support diachronic analysis of façade transformations. A high-accuracy reference survey integrating Terrestrial Laser Scanning and Close- Range Photogrammetry was carried out on a limited portion of the block to validate the rapid survey results. Different ground control configurations were evaluated to assess the trade-off between acquisition speed and metric accuracy. All survey products and diachronic imagery were integrated into a GIS-based information system structured according to the Carta del Rischio data model. The system enables immersive visualization of panoramic images, metric inspection of façade orthophotos, and structured data management, supporting monitoring, risk assessment, and conservation activities in historic urban contexts.

This article addresses the challenges of conducting integrated 3D surveys of complex historic architecture, focusing on the documentation and modelling of the Basilica of Santa Maria della Steccata in Parma (Italy). The Basilica’s impressive scale, rich decorative features, and complex architectural layout – including a network of secondary spaces and attics accessible only through narrow, meandering paths – posed significant challenges for the survey. To overcome these obstacles, an integrated approach combining Terrestrial Laser Scanning (TLS), Close-Range Photogrammetry (CRP), Spherical Photogrammetry (SP), and UAV Photogrammetry was employed. The article outlines the planning, execution, and processing phases of the survey campaign, with particular emphasis on the methodological issues involved in merging data from multiple sources in such a constrained and heterogeneous environment. In this context, the article introduces and evaluates an ICP-assisted Bundle Block Adjustment (ICP-BBA) strategy designed to improve CRP- and TLS-derived models, demonstrating its effectiveness in enhancing local consistency in areas prone to residual misalignments. In addition, the performance of SP is examined under varying spatial conditions, highlighting its potential both as a supplementary method for areas with restricted accessibility and as a stand-alone alternative in specific use cases.