Urban morphology is important in a broad range of investigations across the fields of city planning, transportation, climate, energy, and urban data science. Characterising buildings with a set of numerical metrics is fundamental to studying the urban form. Despite the rapid developments in 3D geoinformation science, and the growing 3D data availability, most studies simplify buildings to their 2D footprint, and when taking their height into account, they at most assume one height value per building, i.e. simple 3D. We take the first step in elevating building metrics into full/true 3D, uncovering the use of higher levels of detail, and taking into account the detailed shape of a building. We set the foundation of the new research line on 3D urban morphology by providing a comprehensive set of 3D metrics, implementing them in openly released software, generating an open dataset containing 2D and 3D metrics for 823,000 buildings in the Netherlands, and demonstrating a use case where clusters and architectural patterns are analysed through time. Our experiments suggest the added value of 3D metrics to complement existing counterparts, reducing ambiguity, and providing advanced insights. Furthermore, we provide a comparative analysis using different levels of detail of 3D building models.

While there exist international standards for geospatial metadata (ISO 19115), these are rarely used in practice for 3D datasets, and one of the OGC standards for 3D city models, CityGML, does not offer a mechanism to store metadata in a structured way. Having metadata in CityGML files, which are in practice often very large and complex, would provide us with the ability to quickly understand the nature of a dataset and to determine if it is relevant for a specific task. A lack of metadata introduces uncertainty into models that are already full of assumptions and estimations. In this paper, we first examine the metadata needs that are specific for 3D geographical datasets and propose ISO 19115 compliant categories. We then describe how these can be used within CityGML by defining an Application Domain Extension (ADE), which allows us to store metadata for existing city objects of CityGML, as well as objects in other domain-specific ADEs. Our ADE, its schema in both UML and XSD, and sample datasets is openly accessible, and it can be easily extended to support application specific metadata. In addition the metadata elements have been added to the core of CityJSON. We also offer software to generate automatically many of the metadata categories and we propose coupling it with the source 3D dataset.

The relatively new Open Geospatial Consortium (OGC) standard LandInfra documents in its data model land and civil engineering infrastructure features. It has a Geography Markup Language (GML) implementation, OGC InfraGML, which has essentially no software support and is rarely used in practice. In order to share the benefits of LandInfra (and InfraGML) with a wider public, we have created the Infra Application Domain Extension (ADE), a CityGML ADE that allows us to store LandInfra features in CityGML. In this paper, we semantically map LandInfra to CityGML, describe our ADE, and discuss a few used cases where our ADE can be useful for applications for the built environment. We also provide software to automatically convert datasets from InfraGML to CityGML (and our ADE), and vice versa, as well as to validate them, which will help practitioners generate real-world InfraGML datasets.

Historical maps are increasingly used for studying how cities have evolved over time, and their applications are multiple: understanding past outbreaks, urban morphology, economy, etc. However, these maps are usually scans of older paper maps, and they are therefore restricted to two dimensions. We investigate in this paper how historical maps can be ‘augmented’ with the third dimension so that buildings have heights, volumes, and roof shapes. The resulting 3D city models, also known as digital twins, have several benefits in practice since it is known that some spatial analyses are only possible in 3D: visibility studies, wind flow analyses, population estimation, etc. At this moment, reconstructing historical models is (mostly) a manual and very time-consuming operation, and it is plagued by inaccuracies in the 2D maps. In this paper, we present a new methodology to reconstruct 3D buildings from historical maps, we developed it with the aim of automating the process as much as possible, and we discuss the engineering decisions we made when implementing it. Our methodology uses extra datasets for height extraction, reuses the 3D models of buildings that still exist, and infers other buildings with procedural modelling. We have implemented and tested our methodology with real-world historical maps of European cities for different times between 1700 and 2000.

Flooding and other natural disasters pose risks to cities and residential homes, and these are set to increase in the face of climate change. Single-family residential buildings are of particular interest because they are difficult to insure and often highlight wealth discrepancies in society in the wake of natural disasters. Calculating building replacement cost based on a specific natural disaster is of interest to municipalities and city planners who are working to prepare their cities for potential future costs of recovery. There are models designed by flood modellers, and there are models designed by city planners. This paper presents a novel Indicator Modelling Framework (IMF) by bringing together a model from the flooding domain (HAZUS) and a model from the geospatial application domain (e.g. CityGML) and weaving them together. The weaving process automatically calculates the building replacement cost for buildings based on a flood scenario as well as generates domain-specific metadata. The weaving process capitalizes on the strengths of both models, and future work will focus on weaving between models in other domains.

The Level of Detail (LOD) concept in CityGML 2.0 is meant to differentiate the multiple representations of semantic 3D city models. Despite the popularity and general acceptance of the concept by the practitioners and stakeholders in 3D city modelling, there are still some limitations. While the CityGML LOD concept is well defined for buildings, bridges, tunnels, and to some extent for roads, there is no clear definition of LODs for terrain/relief, vegetation, land use, water bodies, and generic city objects in CityGML. In addition, extensive research has been done to refine the LOD concept of CityGML for buildings but little is known on requirements and possibilities to model city object types as terrain at different LODs. To address this gap, we focus in this paper on the terrain of a 3D city model and propose a framework for modelling terrains at different LODs in CityGML. As a proof of concept of our framework, we implemented a software prototype to generate terrain models with other city features integrated (e.g. buildings) at different LODs in CityGML.