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 Singapore Government has embarked on a project to establish a three-dimensional city model and collaborative data platform for Singapore. The research herein contributes to this endeavour by developing a methodology and algorithms to automate the conversion of Building Information Models (BIM), in the Industry Foundation Classes (IFC) data format, into CityGML building models, capturing both geometric and semantic information as available in the BIM models, and including exterior as well as interior structures. We adopt a Triple Graph Grammar (TGG) to formally relate IFC and CityGML, both semantically and geometrically, and to transform a building information model, expressed as an IFC object graph, into a city model expressed as a CityGML object graph. The work pipeline includes extending the CityGML data model with an Application Domain Extension (ADE), which allows capturing information from IFC that is relevant in the geospatial context but at the same time not supported by CityGML in its standard form. In this paper, we elaborate on the triple graph grammar approach and the motivation and roadmap for the development of the ADE. While a fully complete and lossless conversion may never be achieved, this paper suggests that both a TGG and an ADE are natural choices for supporting the conversion between IFC and CityGML.

3D city models are omnipresent in urban management and simulations. However, instruments for their evaluation have been limited. Furthermore, current instances are scattered worldwide and developed independently, hampering their comparison and understanding practices. While there are developed assessment frameworks in open data, such efforts are generic and not applied to geospatial data. We establish a holistic and comprehensive four-category framework ‘3D City Index’, encompassing 47 criteria to identify key properties of 3D city models, enabling their assessment and benchmarking, and suggesting usability. We evaluate 40 authoritative 3D city models and derive quantitative and qualitative insights. The framework implementation enables a comprehensive and structured understanding of the landscape of semantic 3D geospatial data, as well as doubles as an evaluated collection of open 3D city models. For example, datasets differ substantially in their characteristics, having heterogeneous properties influenced by their different purposes. There are further applications of this first endeavour to standardise the characterisation of 3D data: monitoring developments and trends in 3D city modelling, and enabling researchers and practitioners to find the most appropriate datasets for their needs. The work is designed to measure datasets continuously and can also be applied to other instances in spatial data infrastructures.