## 1 Introduction  
The creation of digital models (or digital twins [1]) has become a hot topic, especially since the advent of BIM (Building Information Management) [2]. An accurate and complete digital model of a building is the cornerstone of data management of all BIM participants in the construction process [3, 4], necessitating the use of geodetic methods. These methods provide sufficient accuracy for producing digital models in the mandatory regional coordinate system legislatively prescribed for data management. Laser scanning [5] and photogrammetry [6] undoubtedly count among the main geodetic methods for creating a digital model. Both these mass data collection methods can be static or mobile, depending on whether the sensor is mounted on a mobile platform (ground vehicle, airborne carrier) or not. Ground-based data acquisition (static) usually excels in high accuracy and complexity (completeness) of the resulting model, as reported, e.g., by [7, 8]. Aerial data acquisition, in turn, is highly suitable for large objects or areas [9, 10, 11], where fast acquisition is necessary, but is not suitable for interiors or parts of the objects that are obstructed in the aerial view (such as pillars of a bridge structure) due to the lack of a GNSS location signal; however, this obstacle can also be overcome as shown, e.g., in [12, 13, 14]. Mobile data collection partly combines the speed of aerial data collection with the complexity of ground-based data collection [15, 16] at the cost of slightly worse accuracy, as shown in [17, 18]. Photogrammetric methods have also become very popular lately. These methods depend mainly on the sensor and good illumination of the object. As a rule, they benefit from relatively low acquisition costs of the sensor itself, but quite a few prerequisites must be met to produce a usable point cloud, such as suitable sensing methodology [19], the choice of ground control points (GCPs) [20], the selection of the sensor (based on the required ground sampling distance) [21], etc. The used software can undoubtedly also influence the quality of the resulting model [22]. In some cases, however, even seemingly correctly performed measurements fail to yield satisfactory results--for example, the model may be distorted, or the image correlation may be unsuccessful. Consequently, it is always advisable to perform a verification of the model using classical geodetic methods or another bulk data collection method [23]. Compared to photogrammetry, laser scanning is generally associated with higher acquisition costs of the equipment, but if the technology is used correctly, the resulting digital model is usually correct in shape [24]. Point clouds are registered (combined) using control points or direct cloud-to-cloud algorithms (such as the iterative closest point, ICP, algorithm) [25; 26]. This technology can be used at night; if this is the case, however, the colors of the points are incorrectly presented, unless additional illumination is used. Bridge structures are often complicated objects for data collection [27] as they can be relatively long and tall, contain both horizontal and vertical elements, and often are curved in shape [28]. Importantly, considering extremely high requirements on the life span of bridges, the accuracy requirements on geodetic measurements of such objects are typically very high [29]. The progress in the field of laser scanning brought about the development of SLAM (Simultaneous Localization and Mapping) scanners, the use of which can be potentially advantageous for some types of bridge structures. This technology works by using laser rangefinders, usually mounted on a rotating head, and an IMU (inertial measurement unit). The combination of data acquired from both sensors is then used to create a point cloud characterizing the environment while determining the trajectory of the entire system based on the knowledge of its previous position and newly acquired sensor data.