University campuses consists of many buildings within a large area managed by a single organization. Like 3D city modeling, a 3D model of campuses can be utilized to provide a better foundation for planning, navigation and management of buildings. This study approaches 3D modeling of the UTM campus by utilizing data from aerial photos and site observations. The 3D models of buildings were drawn from building footprints in SketchUp and converted to CityGML using FME software. The CityGML models were imported into a geodatabase using 3DCityDB and visualized in Cesium. The resulting 3D model of buildings was in CityGML format level of detail 2, consisting of ground, wall and roof surfaces. The 3D models were positioned with real-world coordinates using the geolocation function in SketchUp. The non-spatial attributes of the 3D models were also stored in a database managed by PostgreSQL. While the methodology demonstrated in this study was found to be able to create LoD2 building models. However, issues of accuracy arose in terms of building details and positioning. Therefore, higher accuracy data, such as point cloud data, should produce higher LoD models and accurate positioning.

Topological properties of objects should be maintained and preserved to concisely represent objects. However, the implementation of 2D topological rules requires the decomposition of 3D objects into lower dimensions to determine topological relationships. This results in 2D topological relationships although the connected objects are in 3D. Hence, accurate representation of 3D connectivity in 3D models is limited. 3D topological rules can be implemented to include topological connectivity in 3D space. This paper implemented an extension of the 27-Intersection Model (27-IM) called the 36-Intersection Model (36-IM) to represent 3D topological adjacencies of two objects in 3D space. This resulted in a 12 × 3 intersection matrix or 36-IM that represented the intersections in terms of dimension and number of separations. Six cases were tested, consisting of “meets”, “disjoint” “intersects at a line”, “intersects at a point”, “contains”, and “overlaps”. The resulting 36-IM matrices provided an accurate representation of how the objects in 3D space were related and their dimension of intersections. The formalisms of the 36-IM matrices were also interoperable which allowed the interpretation of 36-IM using the 9IM and DE-9IM to determine general topological relationships. By examining the intersection of interiors, boundaries and exteriors of 3D objects without object decomposition, 3D topological relationships can be determined as well as the dimension and manner of intersection.

3D city model is a representation of urban area in digital format that contains building and other information. The current approaches are using photogrammetry and laser scanning to develop 3D city model. However, these techniques are time consuming and quite costly. Besides that, laser scanning and photogrammetry need professional skills and expertise to handle hardware and tools. In this study, videogrammetry is proposed as a technique to develop 3D city model. This technique uses video frame sequences to generate point cloud. Videos are processed using EyesCloud3D by eCapture. EyesCloud3D allows user to upload raw data of video format to generate point clouds. There are five main phases in this study to generate 3D city model which are calibration, video recording, point cloud extraction, 3D modeling and 3D city model representation. In this study, 3D city model with Level of Detail 2 is produced. Simple query is performed from the database to retrieve the attributes of the 3D city model.

Spatial databases are a key component of 3D applications that require the storage, management, and manipulation of 3D objects. Topological information that describes the containment, adjacency, and connectivity of objects within a 3D space is crucial for complex spatial analysis. The need to maintain optimal storage and computation within spatial databases recommends the use of lightweight approaches such as topology rules and models. However, current spatial databases use 2D topology mechanisms and limited 3D topology functions. This study conducted experiments on existing topology rules and models within ArcGIS and Oracle spatial database. Additional 3D topology rules were also implemented to determine topological relationships between 3D objects stored in Oracle. The 3D topology rules were based on a 36-Intersection Model (36IM) that describes intersections between objects from 0D to 3D. Based on the experiments, the 2D geodatabase topology rules within ArcGIS were able to determine topological relationships between the objects stored as 2D multi-surfaces datatype. The 2D topology rules and the topology model within Oracle were also unable to support topological relationships between 3D objects. The addition of 36IM topology rules could determine topological relationships and describe the dimensions of intersections. Evidently, the support for 3D topology within spatial databases depends on the availability of 3D datatypes. Most databases that support 3D datatypes have limited support for 3D topology, whereby existing topology mechanisms require the decomposition of 3D objects. The use of 3D topology rules supports the maintenance of topological information without breaking down 3D objects into lower dimension components.

The demand for 3D city modelling for various applications continue to grow with the capabilities of 3D city modelling. One of the uses of 3D city models is to facilitate 3D analysis which usually requires information regarding the topology of the objects within the city model. CityGML as the international standard for 3D city modelling maintains topological information with the use of a 'topology-incidence' where objects are referenced to each other with the condition that the objects share a common surface. This paper explains the extraction of topological information based on the data structure of the geometries in CityGML files and discusses the usability of the existing topology mechanism of CityGML. The topological information was extracted from the CityGML files using the hierarchical geometric structure of CityGML as a stand-in model to describe the topological properties of the object. The extracted information consisted of building surfaces which have been decomposed to 0D points with their respective identification and coordinates. Based on the extracted topological information and related literature, it was found that the topological information extracted from the geometric structure of CityGML was limited to the locality of the object in question and could not extend beyond the dimension of the primitive.

Urbanization has sparked an increase in the construction of multi-use highrise buildings which consists of commercial parcels on their lower floors and residential parcels on their higher floors. In contrast to conventional landed houses, the residents of high-rise buildings share common facilities and private parcels or spaces also differ according to ownership or use. The management and maintenance of these spaces are dependent on the ownership of the parcel where each ownership adheres to different rights, restrictions, and responsibilities (RRRs). Therefore, accurate representation and identification of those parcels affected by maintenance or renovation is crucial for assisting management bodies to improve the quality of life within a multi-use high-rise building. This study attempts to implement a temporal maintenance management for highrise building parcels within a 3D spatial database. A 3D space segmentation was done to analyze the ownership and use of space in a high-rise building. Spatial queries were also performed based on the temporal maintenance of the parcels; in addition, 3D spatial relationships were used to determine adjacent parcels that were affected by the maintenance. Thus, the implementation of temporal strata database management with an accurate 3D representation of the space can provide management bodies with concise and comprehensive information on parcels with respect to ownerships and uses.