The current three-dimensionally (3D) delimited property units are in most countries registered using two-dimensional (2D) documentation and textual descriptions. This approach has limitations if used for representing the actual extent of complicated 3D property units, in particular in city centers. 3D digital models such as building information model (BIM) and 3D geographic information system (GIS) could be utilized for accurate identification of property units, better representation of cadastral boundaries, and detailed visualization of complex buildings. To facilitate this, several requirements need to be identified considering organizational, legal, and technical aspects. In this study, we formulate these requirements and then develop a framework for integration of 3D cadastre and 3D digital models. The aim of this paper is that cadastral information stored based on the land administration domain model (LADM) are integrated with BIM on building level for accurate representation of legal boundaries and with GIS on city level for visualization of 3D cadastre in urban environments. The framework is implemented and evaluated against the requirements in a practical case study in Sweden. The conclusion is that the integration of the cadastral information and BIM/GIS is possible on both conceptual level and data level which will facilitate that organizations dealing with cadastral information (cadastral units), BIM models (architecture, engineering, and construction companies), and GIS (surveying units on e.g., municipality level) can exchange information; this facilitates better representation and visualization of 3D cadastral boundaries.

The integration of 3D city models with Building Information Models (BIM), coined as GeoBIM, facilitates improved data support to several applications, e.g., 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e., harmonization of features, interoperability, format conversions, integration of procedures. The GeoBIM benchmark 2019, funded by ISPRS and EuroSDR, evaluated the state of implementation of tools addressing some of those issues. In particular, in the part of the benchmark described in this paper, the application of georeferencing to Industry Foundation Classes (IFC) models and making consistent conversions between 3D city models and BIM are investigated, considering the OGC CityGML and buildingSMART IFC as reference standards. In the benchmark, sample datasets in the two reference standards were provided. External volunteers were asked to describe and test georeferencing procedures for IFC models and conversion tools between CityGML and IFC. From the analysis of the delivered answers and processed datasets, it was possible to notice that while there are tools and procedures available to support georeferencing and data conversion, comprehensive definition of the requirements, clear rules to perform such two tasks, as well as solid technological solutions implementing them, are still lacking in functionalities. Those specific issues can be a sensible starting point for planning the next GeoBIM integration agendas.

The integration of geoinformation with BIM (GeoBIM) is critical to underpin solutions to many city-related challenges. However, to achieve an effective integration it is necessary to consider not only data and technical options but also current practice and users’ needs. This paper describes work carried out within the EuroSDR-GeoBIM project to address this challenge. After investigating potential uses for GeoBIM and existing challenges, we address a planning permits for buildings use case, to help bridging the gap between theory and practice. The resultshighlights a high-level harmonised workflow envisaging the use of GeoBIM information for automating the planning permits process.

New methods are needed to automate cartographic generalization. This article presents a method for automating the displacement of vector data, called the constraint method. The framework of the method consists of five displacement behavior types. Each cartographic object type belongs to one of these displacement behavior types, which determines the properties of the object type in the displacement process. The displacement behavior types are specified by a set of rules called constraints. The constraint method works as follows. First, it is determined which objects should participate in the displacement process. Then, for each object a set of constraints is set up, depending on its displacement behaviour type. All the constraints build up an overdetermined equation system. This equation system gives how much each object must be moved and/or distorted to solve the spatial conflict. The paper concludes with two applications.