In this paper, we present our workflow to automatically reconstruct three-dimensional (3D) building models based on two-dimensional building polygons and a lidar point cloud. The workflow generates models at different levels of detail (LoDs) to support data require-ments of different applications from one consistent source. Specific attention has been paid to make the workflow robust to quickly run a new iteration in case of improvements in an algorithm or in case new input data become available. The quality of the reconstructed data highly depends on the quality of the input data and is monitored in several steps of the process. A 3D viewer has been developed to view and download the openly available 3D data at different LoDs in different formats. The workflow has been applied to all 10 million buildings of the Netherlands. The 3D ser-vice will be updated after new input data becomes available.

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Level of Detail (LoD) is a well known concept in 3D city models, used to designate different geometric detail that can be used in different applications. Nevertheless, multi-LoD datasets are hard to maintain and manage because of their intrinsic complexity. Versioning is a solution that aids in the storage and management of big and complex dataset, with its main goal being to facilitate the tracking of changes and collaboration. In this paper, we investigate the effects of utilising versioning and, more specifically, the concept of branches as a way to manage the evolution of multi-LoD datasets. We propose a framework according to which every LoD is stored in its own branch and can be extracted and updated independently. We tested this framework on a tile from 3D BAG, a dataset of 3D buildings for the whole of the Netherlands containing four LoDs (namely, LoD0, LoD1.2, LoD1.3 and LoD2.2). Our results suggest that there are certain benefits from this solution, such as the efficient tracking of changes for individual LoDs and the ability to extract and update the model using one LoD at a time. Nevertheless, there is a lot of complexity added to the process as a set of rules needs to be enforced when managing the model.

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Roads are important for many urban planning applications, such as traffic modelling and delivery vehicle routing. At present, most available datasets represent roads only as centrelines. This is particularily true for OpenStreetMap which provides, among many features, road networks at worldwide coverage. Furthermore, most approaches for creating more detailed networks, such as carriageways or lanes, focus on doing so from sources that are not easy to acquire, such as satellite imagery or LiDAR scans. In this paper we present a methodology to create carriageways based on OpenStreetMap's centrelines and open access areal representations (i.e. polygons) to determine which roads should be represented as two individual carriageways. We applied our methodology in five areas across four different countries with different built environments. We analysed the outcome in a delivery routing problem to evaluate the validity of our results. Our results suggest that this method can be effectively applied to create carriageways anywhere in the world, as long as there is sufficient coverage by OpenStreetMap and an areal representation dataset of roads.

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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.@en

3D-toepassingen gaan vaak gepaard met de wens om gebouwen met dakvormen te modelleren. Na jaren onderzoek en ontwikkeling hebben we in Delft een methode gerealiseerd die volledig automatisch dakvormen (LoD2) reconstrueert uit puntenwolken en 2D-pandpolygonen. Met deze methode hebben we 3D-modellen gegenereerd voor alle 10 miljoen BAG-panden in Nederland, de eerste open 3D-dataset op dit detailniveau. Niet alle toepassingen zijn gebaat bij dit detailniveau. Daarom reconstrueren we in hetzelfde proces ook andere detailniveaus. Het volledig automatisch proces zorgt ook in de toekomst voor consistentie als nieuwe modellen worden geconstrueerd met actuele input-data. Bovendien monitoren we verschillende kwaliteitsparameters die gebruikers kunnen helpen bij de juiste toepassing van de data. @en

Climate change and urbanization rates are transforming urban environments, making the use of 3D city models in computational fluid dynamics (CFD) a fundamental ingredient to evaluate urban layouts before construction. However, current geometries used in CFD simulations tend to be built by CFD experts to test specific cases, most of the times oversimplifying their designs due to lack of information or in order to reduce complexity. In this work we explore what are the effects of oversimplifying geometries by comparing wind simulations of different level of detail geometries. We use semantic 3D city models automatically built and adjust them to their suitable use in CFD. For the first test, we explore wind simulations within a troublesome section of the TUDelft campus, the passage next to the EWI building (the tallest building in our domain), where the use of 3D city model variants show how differences in geometry and surface properties affect local wind conditions. Finally we analyze what these differences in velocity magnitude could mean for practitioners in terms of pedestrian wind comfort.

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Fully automated reconstruction of high-detail building models on a national scale is challenging. It raises a set of problems that are seldom found when processing smaller areas, single cities. Often there is no reference, ground truth available to evaluate the quality of the reconstructed models. Therefore, only relative quality metrics are computed, comparing the models to the source data sets. In the paper we present a set of relative quality metrics that we use for assessing the quality of 3D building models, that were reconstructed in a fully automated process, in Levels of Detail 1.2, 1.3, 2.2 for the whole of the Netherlands. The source data sets for the reconstruction are the Dutch Building and Address Register (BAG) and the National Height Model (AHN). The quality assessment is done by comparing the building models to these two data sources. The work presented in this paper lays the foundation for future research on the quality control and management of automated building reconstruction. Additionally, it serves as an important step in our ongoing effort for a fully automated building reconstruction method of high-detail, high-quality models.

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As web applications become more popular, 3D city models would greatly benefit from a proper web-based solution to visualise and manage them. CityJSON was introduced as a JSON encoding of the CityGML data model and promises, among several benefits, the ability to be integrated with modern web technologies. In order to provide an implementation of a web application for CityJSON data, that can be used as a reference for other applications, we developed <code>ninja</code>. It is a web application that allows the user to easily load and investigate a CityJSON model through a web browser. In addition, it offers support for a complex feature of CityJSON: the experimental versioning mechanism. In this paper, we describe the motivation, requirements, technical aspects and achieved functionality of <code>ninja</code>. We believe that such a web application can facilitate the adoption of 3D city models by more practitioners and decision makers.

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When QGIS 3.0 was released in 2018, it added support for 3D visualisation. At the same time, CityJSON has been developing as an easy‐to‐use JavaScript Object Notation (JSON) encoding for 3D city models using the CityGML 2.0 data model. Together, this opened the possibility to support semantic 3D city models in the popular open‐source GIS software for the first time. In order to add support for 3D city models in QGIS, we have developed a plugin that enables CityJSON datasets to be loaded. The plugin parses a CityJSON file and analyses its tree structure to identify all city objects. Then, the geometry and attributes of every city object are transformed into QGIS features and divided into layers according to user preferences. CityJSON parsing was proven to be straightforward and consistent when tested against several open datasets. One of the biggest challenges we faced, though, was mapping CityJSON’s hierarchical data structure to the relational model of QGIS. We undertook this issue by providing various methods on how geometries from the model are loaded as QGIS features. We intend to use the plugin for educational purposes in our university and we believe it can be proven a worthy tool for researchers and practitioners.@en

OGC CityGML is an open standard for 3D city models intended to foster interoperability and support various applications. However, through our practical experience and discussions with practitioners, we have noticed several problems related to the implementation of the standard and the use of standardized data. Nevertheless, a systematic investigation of these issues has never been carried out, and there is thus insufficient evidence for tackling the problems. The GeoBIM benchmark project is aimed at finding such evidence by involving external volunteers, reporting on various aspects of the behavior of tools (geometry, semantics, georeferencing, functionalities), analyzed and described in this article. This study explicitly pointed out the critical points embedded in the format as an evidence base for future development. A companion article (Part I) describes the results of the benchmark related to IFC, the counterpart of CityGML within building information modeling.

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Semantically enriched 3D city models have the potential to be powerful hubs of integrated information for computer-based urban spatial analysis. This article presents the state of the art in 3D city modelling in the context of broader developments such as smart cities and digital twins, and outlines six challenges that must be overcome before 3D data as a platform becomes a reality.@en

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map’s semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of geometry, topology and semantics by incorporating the C-Map data structure into the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.@en

A 3D city model should be constantly updated with new versions, either to reflect the changes in its real-world counterpart, or to improve and correct parts of the model. However, the current standards for 3D city models do not support versioning, and existing version control systems do not work well with 3D city models. In this paper, we propose an approach to support versioning of 3D city models based on CityJSON and the concepts behind the Git version control system, including distributed and non-linear workflows. We demonstrate the benefits of our approach in two examples and in our software prototype, which is able to extract a given version of a 3D city model and to display its history.@en

The international standard CityGML is both a data model and an exchange format to store digital 3D models of cities. While the data model is used by several cities, companies, and governments, in this paper we argue that its XML-based exchange format has several drawbacks. These drawbacks mean that it is difficult for developers to implement parsers for CityGML, and that practitioners have, as a consequence, to convert their data to other formats if they want to exchange them with others. We present CityJSON, a new JSON-based exchange format for the CityGML data model (version 2.0.0). CityJSON was designed with programmers in mind, so that software and APIs supporting it can be quickly built. It was also designed to be compact (a compression factor of around six with real-world datasets), and to be friendly for web and mobile development. We argue that it is considerably easier to use than the CityGML format, both for reading and for creating datasets. We discuss in this paper the main features of CityJSON, briefly present the different software packages to parse/view/edit/create files (including one to automatically convert between the JSON and GML encodings), analyse how real-world datasets compare to those of CityGML, and we also introduce Extensions, which allow us to extend the core data model in a documented manner.@en

3D city models are being increasingly adopted by organisations in order to serve application needs related to urban areas. In order to fulfil the different requirements of various applications, the concept of Level of Detail (LoD) has been incorporated in 3D city models specifications, such as CityGML. Therefore, datasets of different LoDs are being created for the same areas by several organisations for their own use cases. Meanwhile, as time progresses newer versions of existing 3D city models are being created by vendors. Nevertheless, the existing mechanisms for representating multi-LoD data has not been adopted by the users and there has been little effort on the implementation of a mechanism to store multiple revisions of a city model. This results in redundancy of information and the existence of multiple datasets inconsistent with each other. Alternatively, a representation of time or scale as additional dimensions to the three spatial ones has been proposed as a better way to store multiple versions of datasets while retaining information related to the corresponding features between datasets. In this paper, we propose a conceptual framework with initial considerations for the implementation of a 4D representation of two states of a 3D city model. This framework defines both the data structure of such an approach, as well as the methodology according to which two existing 3D city models can be compared, associated and stored with their correspondences in 4D. The methodology is defined as six individual steps that have to be undertaken, each with its own individual requirements and goals that have to be challenged. We, also, provide some examples and considerations for the way those steps can be implemented.@en

3D city models are becoming increasingly important for applications such as evacuation scenarios and energy consumption estimation. For these applications embedding semantic information on geometry is a key factor. The most popular implementation of modern 3D city models is based on the CityGML data model which describes spatial 3D data using a geometrical representation according to the GML encoding standard. While CityGML supports some basic storage of topological relationships between geometric objects, it fails to offer a true 3D topological representation of the city model. Alternatively, a true topological data structure can be used as an intermediate data model, to enable enforcing certain restrictions and operations that are more efficient for specific applications. In this article, we discuss a method that we have developed for the automatic conversion of CityGML models to a topological structure, while maintaining semantic information that was initially attached to the city objects. Such an approach raises certain challenges, as the geometries are not one-to-one analogous to the topological objects that are needed to represent them. We also provide a few examples that indicate that such a method is not trivial for retaining all information that was initially stored in a city model.@en