Digital 3D capture and reliable reproduction of architectural features is the first and most difficult step towards defining a heritage BIM. Three-dimensional digital survey technologies, such as TLS and photogrammetry, enable experts to scan buildings with a new level of detail. Challenges in the tracing of parametric objects in a TLS point cloud include the reconstruction of occluded parts, measurement of uncertainties relevant to surface reflectivity, and edge detection and location. In addition to image-based techniques being considered cost effective, highly flexible, and efficient in producing a high-quality 3D textured model, they also provide a better interpretation of surface linear characteristics. This article addresses an architecture survey workflow using photogrammetry and TLS to optimize a point cloud that is sufficient for a reliable HBIM. Fusion-based workflows were proposed during the recording of two heritage sites—the Matbouli House Museum in Historic Jeddah, a UNESCO World Heritage Site; and Asfan Castle. In the Matbouli House Museum building, which is rich with complex architectural features, multi-sensor recording was implemented at different resolutions and levels of detail. The TLS data were used to reconstruct the basic shape of the main structural elements, while the imagery’s superior radiometric data and accessibility were effectively used to enhance the TLS point clouds for improving the geometry, data interpretation, and parametric tracing of irregular objects in the facade. Furthermore, in the workflow that is considered to be the ragged terrain of the Castle of Asfan, here, the TLS point cloud was supplemented with UAV data in the upper building zones where the shadow data originated. Both datasets were registered using an ICP algorithm to scale the photogrammetric data and define their actual position in the construction system. The hybrid scans were imported and processed in the BIM environment. The building components were segmented and classified into regular and irregular surfaces, in order to perform detailed building information modeling of the architectural elements. The proposed workflows demonstrated an appropriate performance in terms of reliable and complete BIM mapping in the complex structures.

The study highlights the significance of combining imaging and laser scanning techniques to enrich point clouds used for reliable documentation and Heritage Building Information Modeling (HBIM). The fusion-based approach was used to document Al Ula Heritage site in Saudi Arabia, a UNESCO World Heritage Site with well-preserved tombs from the first century BC. The HBIM parametric modeling process requires a detailed survey to collect all geometric data. Although terrestrial laser scanners (TLS) are an efficient tool for 3D recording of heritage scenes in a short period of time, the data resolution is insufficient for identifying and evaluating the spatial distribution of surface weathering forms. Furthermore, combining scans collected at different times may pose difficulties in recording the texture. These issues have an impact on the subsequent 3D modeling phase as well as the efficiency of interpreting and tracing surface features in the Scan-to-BIM process. The proposed workflow using imagery data to enhance both the geometry and coloring of laser point clouds. In addition to texture mapping, the high-resolution imagery is used to densify the laser data using dense image matching, allowing for a clear reading of the surface features, and serving as a useful tool to identify the type, extent, and severity of façade damage. TLS and imagery data were collected separately, with images taken at the best time and location for realistically recording of surface details. Finally, the captured images are orthorectified by TLS geometric information and used for HBIM texturing to provide realistic decay mapping. The results showed that the combination of TLS and photogrammetry allowed for the efficient collection of 3D data, which improved tracing and digitizing HBIM with complete mapping information. The research findings will be greatly useful in the management and planning of historic building conservation and restoration projects.

LiDAR is considered as an effective technology for digitizing the real scene at a very high-resolution and in a short time. However, the resolution of the LiDAR is not sufficient to identify and evaluate the façade surface features like edges and cracks. Generally, photographs provide a better interpretation of the linear characteristics. The complementary benefits of each allow exploring valuable spatial information with different surface detail levels. The paper introduces a flexible image-based approach for linear feature extraction from LiDAR point cloud. Initially, the algorithm converts the point clouds into a structured depth image to reduce the complexity and computation time. Using transformation matrix and camera calibration parameters, the visible point clouds are perceptively projected into color image space using co-linearity equations. The result depth channel is sampled with the interpolation process and added to the color channels to compute (RGBD) layers. The edges and linear features of the surface are initially extracted using the optical 2D imagery and subsequently, each pixel of the linear features can be projected directly into 3D space. Due to the various acquisition positions of the laser and color images, the issue of occlusion is resolved using the visibility algorithm. Applying the methodology, experimental results from the Treasury Monument of Jordan’s ancient Petra City, indicate that the developed approach provides adequate contour points for better interpretation and quantification of weathering processes and dangerous cracking. 3D Modeling these features can also reduce data size, facilitating surface inspection and analysis with simpler models.

Building information modeling (BIM) has recently become more popular in historical buildings as a method to rebuild their geometry and collect relevant information. Heritage BIM (HBIM), which combines high-level data about surface conditions, is a valuable tool for conservation decision-making. However, implementing BIM in heritage has its challenges because BIM libraries are designed for new constructions and are incapable of accommodating the morphological irregularities found in historical structures. This article discusses an architecture survey workflow that uses TLS, imagery, and deep learning algorithms to optimize HBIM for the conservation of the Nabatean built heritage. In addition to creating new resourceful Nabatean libraries with high details, the proposed approach enhanced HBIM by including two data outputs. The first dataset contained the TLS 3D dense mesh model, which was enhanced with high-quality textures extracted from independent imagery captured at the optimal time and location for accurate depictions of surface features. These images were also used to create true orthophotos using accurate and reliable 2.5D DSM derived from TLS, which eliminated all image distortion. The true orthophoto was then used in HBIM texturing to create a realistic decay map and combined with a deep learning algorithm to automatically detect and draw the outline of surface features and cracks in the BIM model, along with their statistical parameters. The use of deep learning on a structured 2D true orthophoto produced segmentation results in the metric units required for damage quantifications and helped overcome the limitations of using deep learning for 2D non-metric imagery, which typically uses pixels to measure crack widths and areas. The results show that the scanner and imagery integration allows for the efficient collection of data for informative HBIM models and provide stakeholders with an efficient tool for investigating and analyzing buildings to ensure proper conservation.

The work described in the paper emphasizes the importance of integrating imagery and laser scanner techniques (TLS) to optimize the geometry and visual quality of Heritage BIM. The fusion-based workflow was approached during the recording of Zee Ain Historical Village in Saudi Arabia. The village is a unique example of traditional human settlements, and represents a complex natural and cultural heritage site. The proposed workflow divides data integration into two levels. At the basic level, UAV photogrammetry with enhanced mobility and visibility is used to map the ragged terrain and supplement TLS point data in upper and unaccusable building zones where shadow data originated. The merging of point clouds ensures that the building’s overall geometry is correctly rebuilt and that data interpretation is improved during HBIM digitization. In addition to the correct geometry, texture mapping is particularly important in the area of cultural heritage. Constructing a realistic texture remains a challenge in HBIM; because the standard texture and materials provided in BIM libraries do not allow for reliable representation of heritage structures, mapping and sharing information are not always truthful. Thereby, at the second level, the workflow proposed true orthophoto texturing method for HBIM models by combining close-range imagery and laser data. True orthophotos have uniform scale that depicts all objects in their respective planimetric positions, providing reliable and realistic mapping. The process begins with the development of a Digital Surface Model (DSM) by sampling TLS 3D points in a regular grid, with each cell uniquely associated with a model point. Then each DSM cell is projected in the corresponding perspective imagery in order to map the relevant spectral information. The methods allow for flexible data fusion and image capture using either a TLS-installed camera or a separate camera at the optimal time and viewpoint for radiometric data. The developed workflows demonstrated adequate results in terms of complete and realistic textured HBIM, allowing for a better understanding of the complex heritage structures.

Heritage recording has received much attention and benefits from recent developments in the field of range and imaging sensors. While these methods have often been viewed as two different methodologies, data integration can achieve different products, which are not always found in a single technique. Data integration in this paper can be divided into two levels: laser scanner data aided by photogrammetry and photogrammetry aided by scanner data. At the first level, superior radiometric information, mobility and accessibility of imagery can be actively used to add texture information and allow for new possibilities in terms of data interpretation and completeness of complex site documentation. In the second level, true orthophoto is generated based on laser data, the results are rectified images with a uniform scale representing all objects at their planimetric position. The proposed approaches enable flexible data fusion and allow images to be taken at an optimum time and position for radiometric information. Data fusion usually involves serious distortions in the form of a double mapping of occluded objects that affect the product quality. In order to enhance the efficiency of visibility analysis in complex structures, a proposed visibility algorithm is implemented into the developed methods of texture mapping and true orthophoto generation. The algorithm filters occluded areas based on a patch processing using a grid square unit set around the projected vertices. The depth of the mapped triangular vertices within the patch neighborhood is calculated to assign the visible one. In this contribution, experimental results from different historical sites in Jordan are presented as a validation of the proposed algorithms. Algorithms show satisfactory performance in terms of completeness and correctness of occlusion detection and spectral information mapping. The results indicate that hybrid methods could be used efficiently in the representation of heritage structures.