Abstract. Topological relationships between spatial objects represent important knowledge that users of geographic information systems expect to retrieve from a spatial database. A di cult task is to assign precise semantics to user queries involving concepts such as \crosses", \is inside", \is adjacent". In this paper, we present t wo methods for describing topological relationships. The rst method is an extension of the geometric point-set approach b y taking the dimension of the intersections into account. This results in a very large number of di erent topological relationships for point, line, and area features. In the second method, which aims to be more suitable for humans, we propose to group all possible cases into a few meaningful topological relationships and we discuss their exclusiveness and completeness with respect to the point-set approach.

The knowledge of the transportation mode used by humans (e.g. bicycle, on foot, car, and train) is critical for travel behaviour research, transport planning and traffic management. Nowadays, new technologies such as the GPS have replaced traditional survey methods (paper diaries, telephone) since they are more accurate and problems such as underreporting are avoided. However, although the movement data collected (timestamped positions in digital form) have generally high accuracy, they do not contain the transportation mode. We present in this paper a new method for segmenting movement data into single-mode segments and to classify them according to the transportation mode used. Our fully automatic method differs from previous attempts for five reasons: (1) it relies on fuzzy concepts found in expert systems, i.e. membership functions and certainty factors; (2) it uses OpenStreetMap data to help the segmentation and classification process; (3) we can distinguish between 10 transportation modes (incl. between tram, bus, and car) and we propose a hierarchy; (4) it handles data with signal shortages and noise, and other real-life situations; (5) in our implementation, there is a separation between the reasoning and the knowledge, so that users can easily modify the parameters used and add new transportation modes. We have implemented the method and tested it with a 17-million point dataset collected in the Netherlands and elsewhere in Europe. The accuracy of the classification with the developed prototype, determined with the comparison of the classified results with the reference data derived from manual classification, is 91.6 percent.

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INTRODUCTIONGeo-DBMSs make it possible to manage large spatial datasets in databases that can be accessed by multiple users at the same time. These spatial datasets usually contain 2D data, while more and more applications depend on 3D data. Some examples are 3D cadastres [1], telecommunications [2] and town planning [3]. These applications mainly come from the ever-growing tendency of using living space multifunctional by building in the vertical direction, e.g. apartments, buildings over spanning a road, tunnels and bridges [1]. The present Geo-DBMSs do not support 3D primitives, but 3D spatial objects can be modelled by using 2D primitives such as polygons. This is possible by using 3D coordinates, which are supported by the Geo-DBMSs. In this way, several 2D polygons bound a 3D object. These 2D polygons can be stored in one record (multi-polygon) or multiple records.The absence of a real 3D primitive in the Geo-DBMSs however, results into two problems:• The Geo-DBMSs do not recognize 3D spatial objects, because they do not have a 3D primitive to model the 3D object. This results into DBMS functions not working properly (e.g. there is no validation for the 3D object as a whole and functions only work with the projection of these objects, because the third dimension is ignored [4]).• In the case 2D objects, that bound a 3D object, are stored in multiple records, a 1:n relationship exists between the object and the number of records; a better administration of these large datasets requires a 1:1 relationship between objects in reality and objects in the database.Geo-DBMSs were developed to store spatial data, because they could guarantee the safety of the data (in 2D). But with the arrival of applications depending upon correct 3D data, new techniques need to be developed to support 3D data as well. The solution for this problem is to implement a real 3D primitive, including validation functions and functions that e.g. return the volume or the distance in 3D between objects. This improves the maintainability of 3D geo-datasets [5] and opens the door to more realistic applications [2], [3]. This paper will show how 3D spatial objects can be modelled, i.e. stored, validated and queried, in a Geo-DBMS using a 3D primitive and how these objects can be visualised. The innovation of this research is that the developed concepts have been translated into prototype implementations of a true 3D primitive in a DBMS environment (Oracle Spatial 9i Spatial [11]). As far as we know, this is the first time ever that a Geo-DBMS directly supports

Abstract:The aim of this research is to investigate the combined use of IndoorGML and the Land Administration Domain Model (LADM) to define the accessibility of the indoor spaces based on the ownership and/or the functional right for use. The users of the indoor spaces create a relationship with the space depending on the type of the building and the function of the spaces. The indoor spaces of each building have different usage functions and associated users. By defining the user types of the indoor spaces, LADM makes it possible to establish a relationship between the indoor spaces and the users. LADM assigns rights, restrictions, and responsibilities to each indoor space, which indicates the accessible spaces for each type of user. The three-dimensional (3D) geometry of the building will be impacted by assigning such functional rights, and will provide additional knowledge to path computation for an individual or a group of users. As a result, the navigation process will be more appropriate and simpler because the navigation path will avoid all of the non-accessible spaces based on the rights of the party. The combined use of IndoorGML and LADM covers a broad range of information classes: (indoor 3D) cell spaces, connectivity, spatial units/boundaries, (access/use) rights and restrictions, parties/persons/actors, and groups of them. The new specialized classes for individual students, individual staff members, groups of students, groups of staff members are able to represent cohorts of education programmes and the organizational structure (organogram: faculty, department, group). The model is capable to represent the access times to lecture rooms (based on education/teaching schedules), use rights of meeting rooms, opening hours of offices, etc. The two original standard models remain independent in our approach, we do not propose yet another model, but applications can fully benefit of the potential of the combined use, which is an important contribution of this paper. The main purpose of the combined use model is to support the indoor navigation, but could also support different applications, such as the maintenance and facility management work, by computing the cleaning cost based on the space floor area. The main contributions of this paper are: a solution for the combined use of IndoorGML-LADM model, a conceptual enhancement of LADM by the refinement of the LA_Party package with specialization for staff and student (groups), and the assessment of the model by converting sample data (from two complex university buildings) into the model, and conducting actual access-rights aware navigation, based on the populated model.

Much work has already been done on how a 3D Cadastre should best be developed. An inclusive information model, the Land Administration Model (LADM ISO 19152) has been developed to provide an international framework for how this can best be done. This conceptual model does not prescribe the technical data format. One existing source from which data could be obtained is 3D Building Information Models (BIMs), or, more specifically in this context, BIMs in the form of one of buildingSMART's open standards: the Industry Foundation Classes (IFC). The research followed a standard BIM methodology of first defining the requirements through the use of the Information Delivery Manual (IDM ISO29481) and then translating the process described in the IDM into technical requirements using a Model View Definition (MVD), a practice to coordinate upfront the multidisciplinary stakeholders of a construction project. The proposed process model illustrated how the time it takes to register 3D spatial units in a Land Registry could substantially be reduced compared to the first 3D registration in the Netherlands. The modelling of an MVD or a subset of the IFC data model helped enable the creation and exchange of boundary representations of topological objects capable of being combined into a 3D legal space overview map.

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D ata structures supporting variable scale data sets are still very rare. There are a number of data structures available for multi-scale databases based on multiple representations, that is, the data are used for a fixed number of scale (or resolution) intervals. These multiple representation data structures attempt to explicitly relate objects at different scale levels, in order to offer consistency during the use of the data. The drawbacks of the multiple representations data structures are that they do store redundant data (same coordinates, originating from the same source) and that they support only a limited number of scale intervals. Most data structures are intended to be used during the pan and zoom (in and out) operations, and in that sense multi-scale data