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Geographic information and building information modelling both model buildings and infrastructure, but the way in which they are modelled is usually complimentary and BIM-GIS integration is widely considered as a way forward for both domains. For one, more detailed BIM data can feed more general GIS data and GIS data can provide the context that is necessary to BIM data. While previous studies have focused on the theoretical aspects of such an integration at a schema level, in this paper we focus on explaining the geometric and topological issues we have found while trying to develop software to realise such an integration in practice and at a data level. In our preliminary results, which are presented here, we have found that many issues for such an integration remain: handling the geometric and topological problems in BIM models, dealing with bad georeferencing and figuring out the best way to convert data between IFC and CityGML are all open issues.

Road traffic and industrial noise has become a major source of discomfort and annoyance among the residents in urban areas. More than 44 % of the EU population is regularly exposed to road traffic noise levels over 55 dB, which is currently the maximum accepted value prescribed by the Environmental Noise Directive for road traffic noise. With continuously increasing population and number of motor vehicles and industries, it is very unlikely to hope for noise levels to diminish in the near future. Therefore, it is necessary to monitor urban noise, so as to make mitigation plans and to deal with its adverse effects. The 2002/49/EC Environmental Noise Directive aims to determine the exposure of an individual to environmental noise through noise mapping. One of the most important steps in noise mapping is the creation of input data for simulation. At present, it is done semi-automatically (and sometimes even manually) by different companies in different ways and is very time consuming and can lead to errors in the data. In this paper, we present our approach for automatically creating input data for noise simulations. Secondly, we focus on using 3D city models for presenting the results of simulation for the noise arising from road traffic and industrial activities in urban areas. We implemented a few noise modelling standards for industrial and road traffic noise in CityGML by extending the existing Noise ADE with new objects and attributes. This research is a steping stone in the direction of standardising the input and output data for noise studies and for reconstructing the 3D data accordingly.

To be used as input in most simulation and modelling software, 3D city models should be geometrically and topologically valid, and semantically rich. We investigate in this paper what is the quality of currently available CityGML datasets, i.e. we validate the geometry/topology of the 3D primitives (Solid and MultiSurface), and we validate whether the semantics of the boundary surfaces of buildings is correct or not. We have analysed all the CityGML datasets we could find, both from portals of cities and on different websites, plus a few that were made available to us. We have thus validated 40M surfaces in 16M 3D primitives and 3.6M buildings found in 37 CityGML datasets originating from 9 countries, and produced by several companies with diverse software and acquisition techniques. The results indicate that CityGML datasets without errors are rare, and those that are nearly valid are mostly simple LOD1 models. We report on the most common errors we have found, and analyse them. One main observation is that many of these errors could be automatically fixed or prevented with simple modifications to the modelling software. Our principal aim is to highlight the most common errors so that these are not repeated in the future. We hope that our paper and the open-source software we have developed will help raise awareness for data quality among data providers and 3D GIS software producers.

The production and dissemination of semantic 3D city models is rapidly increasing benefiting a growing number of use cases. However, their availability in multiple LODs and in the CityGML format is still problematic in practice. This hinders applications and experiments where multi-LOD datasets are required as input, for instance, to determine the performance of different LODs in a spatial analysis. An alternative approach to obtain 3D city models is to generate them with procedural modelling, which is – as we discuss in this paper – well suited as a method to source multi-LOD datasets useful for a number of applications. However, procedural modelling has not yet been employed for this purpose. Therefore, we have developed RANDOM3DCITY, an experimental procedural modelling engine for generating synthetic datasets of buildings and other urban features. The engine is designed to produce models in CityGML and does so in multiple LODs. Besides the generation of multiple geometric LODs, we implement the realisation of multiple levels of spatiosemantic coherence, geometric reference variants, and indoor representations. As a result of their permutations, each building can be generated in 392 different CityGML representations, an unprecedented number of modelling variants of the same feature. The datasets produced by RANDOM3DCITY are suited for several applications, as we show in this paper with documented uses. The developed engine is available under an open-source licence at Github at http://github.com/tudelft3d/Random3Dcity.

CityGML, an OGC standard, is an open data model for virtual 3D city models and includes buildings, roads, terrain, water bodies, etc. While many modules are well-developed (eg buildings, bridges, tunnels), the transportation model is, based on our consultations with various government agencies and municipalities, not sufficient for most transportation applications. We propose in this paper several improvements to the CityGML v2.0 Transportation module, and to the previous efforts for improving it. Our additions are based on the consultations we had, and on the use-cases that were identified. We argue that the following changes are necessary: A) multi-LoD modelling of roads, B) carriageway representation, C) detailed intersection modelling and, D) introducing waterways as a new sub-class.

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.

In both the Geographic Information (Geo) and Building Information Modelling (BIM) domains, it is widely acknowledged that the integration of data from both domains is beneficial and a crucial step in facing the multi-disciplinary challenges of our built environment. The result of this integration – which can broadly be termed GeoBIM – could answer questions such as identifying an appropriate Heating, Ventilation and Air Conditioning system for a building based on room usage, outside air temperature, solar exposure and traffic pollution or validating whether a proposed built asset meets relevant planning constraints. Developing a coherent approach to GeoBIM integration requires consensus between multiple stakeholders from both the Geo and the BIM side and at an international level. This multi-country and multi-stakeholder approach is the topic of a 2-year EuroSDR project on GeoBIM integration that started in November 2017. The general aim of the project is to detail both the needs and the issues of GeoBIM integration, studied from use cases as well as from existing experiences in the participating countries and to develop initial solutions accordingly. This paper reports initial results – it identifies strong potential for GeoBIM but also rather fragmented activity, with no national level focus. It also notes that research (both in industry and academia) primarily focuses on standards, interoperability and data integration or exchange. Based on these findings – and with a focus on existing work and topics of interest to NMCAs – the next phase of the work will develop more detailed case studies for Asset Management and Urban Planning.

An alternative to the traditional approaches to model separately 2D/3D space, time, scale and other parametrisable characteristics in GIS lies in the higher-dimensional modelling of geographic information, in which a chosen set of non-spatial characteristics, e.g. time and scale, are modelled as extra geometric dimensions perpendicular to the spatial ones, thus creating a higher-dimensional model. While higher-dimensional models are undoubtedly powerful, they are also hard to create and manipulate due to our lack of an intuitive understanding in dimensions higher than three. As a solution to this problem, this paper proposes a methodology that makes nD object generation easier by splitting the creation and manipulation process into three steps: (i) constructing simple nD objects based on nD prismatic polytopes – analogous to prisms in 3D –, (ii) defining simple modification operations at the vertex level, and (iii) simple postprocessing to fix errors introduced in the model. As a use case, we show how two sets of operations can be defined and implemented in a dimension-independent manner using this methodology: the most common transformations (i.e. translation, scaling and rotation) and the collapse of objects. The nD objects generated in this manner can then be used as a basis for an nD GIS.

In addition to buildings, the terrain forms an important part of a 3D city model. Although in GIS terrains are usually represented with 2D grids, TINs are also increasingly being used in practice. One example is 3DTOP10NL, the 3D city model covering the whole of the Netherlands, which stores the relief with a constrained TIN containing more than 1 billion triangles. Due to the massive size of such datasets, the main problem that arises is: how to efficiently store and maintain them? While CityGML supports the storage of TINs, we argue in this paper that the current solution is not adequate. For instance, the 1 billion+ triangles of 3DTOP10NL require 686 GB of storage space with CityGML. Furthermore, the current solution does not store the topological relationships of the triangles, and also there are no clear mechanisms to handle several LODs. We propose in this paper a CityGML extension for the compact representation of terrains. We describe our abstract and implementation specifications (modelled in UML), and our prototype implementation to convert TINs to our CityGML structure. It increases the topological relationships that are explicitly represented, and allows us to compress up to a factor of ∼ 25 in our experiments with massive real-world terrains (more than 1 billion triangles).

Matching of building polygons with different levels of detail is crucial in the maintenance and quality assessment of multi-representation databases. Two general problems need to be addressed in the matching process: (1) Which criteria are suitable? (2) How to effectively combine different criteria to make decisions? This paper mainly focuses on the second issue and views data matching as a supervised pattern classification. Several classifiers (i.e. decision trees, Naive Bayes and support vector machines) are evaluated for the matching task. Four criteria (i.e. position, size, shape and orientation) are used to extract information for these classifiers. Evidence shows that these classifiers outperformed the weighted average approach.