Precise and complete 3D representations of architectural structures or industrial sites are essential for various applications, including structural monitoring or cadastre. However, acquiring these datasets can be time-consuming, particularly for large objects. Mobile scanning systems offer a solution for such cases. In the case of complex scenes, multiple scanning systems are required to obtain point clouds that can be merged into a comprehensive representation of the object. Merging individual point clouds obtained from different sensors or at different times can be difficult due to discrepancies caused by moving objects or changes in the scene over time, such as seasonal variations in vegetation. In this study, we present the integration of point clouds obtained from two mobile scanning platforms within a built-up area. We utilized a combination of a quadruped robot and an unmanned aerial vehicle (UAV). The PointNet++ network was employed to conduct a semantic segmentation task, enabling the detection of non-ground objects. The experimental tests used the Toronto 3D dataset and DALES for network training. Based on the performance, the model trained on DALES was chosen for further research. The proposed integration algorithm involved semantic segmentation of both point clouds, dividing them into square subregions, and performing subregion selection by checking the emptiness or when both subregions contained points. Parameters such as local density, centroids, coverage, and Euclidean distance were evaluated. Point cloud merging and augmentation enhanced with semantic segmentation and clustering resulted in the exclusion of points associated with these movable objects from the point clouds. The comparative analysis of the method and simple merging was performed based on file size, number of points, mean roughness, and noise estimation. The proposed method provided adequate results with the improvement of point cloud quality indicators.

Despite the already advanced work on the construction of jurisdictional 3D cadastre models in many parts of the world and the technical feasibility of building very detailed 3D models of cities, relatively few specialists have focused on the aspects of visualizing property rights in three dimensions. Therefore, to complement the analyses carried out so far in this area, this research aims to investigate the perception of the visualization of multidimensional real estate data using different visual variables and by different audiences. The main contribution of the conducted research to the development of 3D cadastre visualizations is to start a discussion on the differences in their perception among real estate professionals and those who have no experience in this area and may have to use multidimensional property data. The research was conducted using a questionnaire-based survey method with the computer-assisted web interview (CAWI) technique. The questionnaire was completed by students of a course related to real estate law (geodetic science) and those who do not have regular contact with it (environmental engineering, medicine, sports, mechanics, and management). As a result of the survey, it emerged that the group studying geodetic science performed better on average than students in other fields of study. Additionally, the conducted survey confirmed the existing knowledge of the perception of the visualization of property rights in three dimensions. According to it, visualizations of property rights in 3D should use color. The use of transparency helps in visualisations made in grayscale but interferes with more complex colorful objects.

3D cadastral issues have been the subject of scientific research for more than 20 years. However, the initial registration of objects in 3D cadastres remains a significant challenge. The purpose of this study is to verify whether it is possible to register objects for future 3D cadastres based on data from various sources such as laser scanning measurements and technical documentation. The research object is a building in Krakow (Poland). For objects with easy access such as common parts, parking lots, and outer parts of a building, laser scanning was applied. The premises (apartments) are private properties without free access; thus, the technical documentation of the building was used. A 3D model was built in BIM way (Autodesk Revit) based on a terrestrial laser scanning point cloud and technical drawings, but only for the geometrical part of the building. To illustrate the legal relationships among the 3D cadastral objects in the building, a UML model was also created. The results prove that the registration of objects for future 3D cadastres using both methods is possible. However, further research is required.

Motives: In the past twenty years, considerable progress has been made in 3D real estate cadastres and 3D visualisation technologies. These developments require advanced solutions for the visualisation of 3D cadastral objects. Aim: The main aim of this study was to propose an optimal 3D cadastre visualisation strategy that accounts for user needs, the types of visualised data, and visualisation platforms. Results: The optimal 3D cadastre visualisation strategy was determined by performing a SWOT/TOWS analysis. Both internal and external factors that can influence the development of 3D cadastre visualisation policies were considered in the analysis. The results of the study were used to propose an aggressive strategy (based on the identified strengths and opportunities) for the development of 3D cadastre visualisation.