Although level of detail (LoD) is a central concept in 3D city modelling, specifying different LoDs in an unambiguous manner is not straightforward. To resolve this, a set of frameworks have been developed. This paper evaluates the suitability of the LoD framework of (Biljecki et al. 2016) for 3D building models that have been generated directly from BIM models. The output of two BIM shell extractors are tested on how well they can be defined by the framework. It was found that although BIM-derived models can be specified by the framework to a certain degree, the framework is not fully capable to also specify lower quality models and to support all the output that may come from BIM shell extractors. This can be resolved by either addressing issues in the shell extractors’ output or in the framework itself. The results of this research can be used to improve the LoD framework and to adjust the shell extractors output to better comply with unambiguous definitions of building models at different LoDs and could be a first step to standardise the conversion of BIM models at different LoDs to be used in urban applications.@en

GeoBIM, the integration of 3D geoinformation (Geo) with building information models (BIM), is a subject of increasing attention in both domains. A well-known practical challenge for this integration is the mixed state of software support for open standards in each domain that would ease the integration. This is often known by practitioners but poorly documented. In order to solve this problem, we devised the GeoBIM benchmark, in which we compile the experiences of volunteering participants, who perform a guided study to test the software they are most familiar with against a few provided datasets structured in open standards. The aim of the tests is to improve the knowledge of the state of the art in the software support for GeoBIM open standards and to identify points for improvement. In this paper, we present the design of the benchmark, especially explaining and discussing the chosen data to be used with their connected issues to be tested, and some initial results.@en

An investigation into the implementation state of open standards in software is currently ongoing through the ISPRS/EuroSDR ‘GeoBIM benchmark 2019’ initiative, which kicked off earlier this year. The benchmark activity provides a way of assessing and comparing the functionality of different software packages in GIS and BIM in terms of their ability to handle standardised data (IFC and CityGML) and undertake various tasks using this data. Approximately 65 people have registered to participate so far, with participants from a wide range of backgrounds and proposing to test a variety of software packages. This confirms that the issues under investigation are of interest, and also meets the wider benchmark aim of having a variety of participants, since the project is conceived as using a bottom-up approach with cross-disciplinary and cross-expertise participation. While full benchmark results are not due to be submitted until later this year, interim results have highlighted a number of common issues across multiple software packages, and a web meeting for participants held in July 2019 also led to some improvements in how the benchmark results are being captured.@en

The Application Domain Extension (ADE) is a built-in mechanism of CityGML to augment its data model with additional concepts required by particular use cases. The goal of this paper is to provide an overview of the ADE mechanism and a literature review of developments since its introduction a decade ago. The discovery of publications found that currently there are 44 ADEs supporting a wide range of applications, but also application-agnostic purposes such as harmonisation with national geographic information standards. We hope this paper to double as a reference material for the developers of new ADEs.@en

CityGML is the most important international standard used to model cities and landscapes in 3D with extensive semantics. Compared to BIM standards such as IFC, CityGML models are usually less detailed but they cover a much greater spatial extent. They are also available in any of five standardized levels of detail. CityGML serves as an exchange format and as a data source for visualizations, either in dedicated applications or in a web browser. It can also be used for a wide range of spatial analyses, such as visibility studies and solar potential. Ongoing research will improve the integration of BIM standards with CityGML, making improved data exchange possible throughout the life-cycle of urban and environmental processes.@en

Background: The VI-Suite is a free and open-source addon for the 3D content creation application Blender, developed primarily as a tool for the contextual and performative analysis of buildings. Its functionality has grown from simple, static lighting analysis to fully parametric lighting, shadowing, and building energy analyses. It adopts a flexible, mesh geometry based approach to the specification of calculation points and this has made it suitable for certain types of 3D geospatial analyses and data visualisation. Results: As this is the first academic paper to discuss the VI-Suite, a history of its development is presented along with a review of its capabilities of relevance to geospatial analysis. As the VI-Suite combines the functionality of 3D design software with performance simulation, some of the benefits of this combination are discussed including aspects that make it suitable for the processing and analysis of potentially large geospatial datasets. Example use cases with a 3D city model of the Hague are used to demonstrate some of the geospatial workflows possible and some of the result visualisation options. Conclusions: The free and open-source nature of the VI-Suite, combined with the use of Blender mesh geometry to define calculation points, has encouraged usage scenarios not originally intended by the authors, for example large scale urban shadow and radiation analyses. The flexibility inherent in this mesh based approach enables the analysis of large geospatial datasets by giving the user refined control over the distribution of calculation points within the model. The integration of GIS analysis into a digital design package such as Blender offers advanced geometry/material editing and specification, provides tools such as ray casting and BVH tree generation to speed up the simulation of large datasets, and enhanced visualisation of GIS simulation data including animated city fly-throughs and high quality image production. The VI-Suite is part of a completely open-source tool chain and contributions from the community are welcome to further enhance its current geospatial data capabilities.@en

Elevation datasets (e.g. point clouds) are an essential but often unavailable ingredient for the construction of 3D city models. We investigate in this paper to what extent can 3D city models be generated solely from 2D data without elevation measurements. We show that it is possible to predict the height of buildings from 2D data (their footprints and attributes available in volunteered geoinformation and cadastre), and then extrude their footprints to obtain 3D models suitable for a multitude of applications. The predictions have been carried out with machine learning techniques (random forests) using 10 different attributes and their combinations, which mirror different scenarios of completeness of real-world data. Some of the scenarios resulted in surprisingly good performance (given the circumstances): we have achieved a mean absolute error of 0.8m in the inferred heights, which satisfies the accuracy recommendations of CityGML for LOD1 models and the needs of several GIS analyses. We show that our method can be used in practice to generate 3D city models where there are no elevation data, and to supplement existing datasets with 3D models of newly constructed buildings to facilitate rapid update and maintenance of data.@en

3D city models are characterised by the level of detail (LOD), which indicates their spatio-semantic complexity. Modelling data in finer LODs results in visually appealing models and opens the door for more applications, but that is at the expense of increased costs of acquisition, and larger storage footprint. In this paper we investigate whether the improvement in the LOD of a 3D building model brings more accurate shadow predictions. The result is that in most cases the improvement is negligible. Hence, the higher cost of acquiring 3D models in finer LODs is not always justified. However, the exact performance is influenced by the architecture of a building. The paper also describes challenges in experiments such as this one. For instance, defining error metrics may not always be simple, and the big picture of errors should be considered, as the impact of errors ultimately depends on the intended use case. For example, an error of a certain magnitude in estimating the shadow may not significantly affect visualisation purposes, but the same error may considerably influence the estimation of the photovoltaic potential.@en

‘Level of Detail’ (LoD) is een veel gebruikt begrip in de 3D-geoinformatie wereld. Het detailniveauvan 3D-data speelt een rol bij de verschillende stappen in de 3D informatie keten, van inwinning tot gebruik. LoD is ook een van de belangrijkste basisprincipes van de internationale standaard CityGML, waarop de optionele 3D uitbreiding van IMGeo is gebaseerd. Afhankelijk van de toepassing modelleert deze standaard 3D-data op hoog of laag detailniveau. Maar in praktijk roept het gebruik van het detailniveau van stadsmodellen nog veel vragen op.@en

This article reports on the first 3D cadastral registration in The Netherlands, accomplished in March 2016. The solution was sought within the current cadastral, organisational, and technical frameworks to obtain a deeper knowledge on the optimal way of implementing 3D registration, while avoiding discussions between experts from different domains. The article presents the developed methodology to represent legal volumes in an interactive 3D visualisation that can be registered in the land registers. The source data is the 3D Building Information Model (BIM). The methodology is applied to two cases: (1) the case of the railway station in Delft, resulting in the actual 3D registration in 2016; and (2) a building complex in Amsterdam, improving the Delft-case and providing the possibility to describe a general workflow from design data to a legal document. An evaluation provides insights for an improved cadastral registration of multi-level property rights. The main conclusion is that in specific situations, a 3D approach has important advantages for cadastral registration over a 2D approach. Further study is needed to implement the solution in a standardised and uniform way, from registration to querying and updating in the future, and to develop a formal registration process accordingly.@en

The concept of level of detail (LOD) describes the content of 3D city models and it plays an essential role during their life cycle. On one hand it comes akin to the concepts of scale in cartography and LOD in computer graphics, on the other hand it is a standalone concept that requires attention. LOD has an influence on tendering and acquisition, and it has a hand in storage, maintenance, and application aspects. However, it has not been significantly researched, and this PhD thesis fills this void. This thesis reviews dozens of current LOD standards, revealing that most practitioners consider the LOD to be comprised solely of the geometric detail of data and there are disparate views on the concept as a whole. However, the research suggests that the LOD encompasses additional metrics, such as semantics and texture. The thesis formalises the concept, enabling integration and comparison of current LOD standards. The established framework may be applied to cartography and to different forms of 3D geoinformation such as point clouds. Following the formalised concept, a new LOD specification is presented improving the LOD concept in the current OGC CityGML 2.0 standard, a prominent norm in the 3D GIS industry. The specification introduces 16 LODs for buildings that are shaped after analysing the capabilities of acquisition techniques and a large number of real-world datasets. The improved LOD specification may be integrated in product portfolios and tenders, preventing misunderstandings between stakeholders, and as a better language for communicating the specifics of a dataset to be acquired. The specification also considers different approaches to realise the data. Such geometric references result in dozens of different variants of the same LOD. 3D data according to the LOD specification was generated using a procedural modelling engine that was developed over the course of the research. The engine is capable of producing 3D city models in a large number of different variants and according to the CityGML standard. The thesis also catalogues the many different ways to create 3D city models. A prominent technique for producing data in a different LOD is generalisation, i.e. simplifying a 3D city model. The inverse---augmenting the LOD of a dataset---has not been researched to a great extent, and this thesis gives an overview of the topic. This research demonstrates that it is possible to generate 3D city models without elevation measurements, inherently augmenting the LOD of coarser data (2D footprints). The method relies on machine learning: several attributes found in 2D datasets may hint at the height of a building, thus enabling extrusion and creating 3D city models suited for several applications. Some acquisition techniques may result in multi-LOD datasets, and nowadays there are some regions represented in different, independent datasets. However, it was found that possibilities to link such data are deficient. The lack of linking mechanisms inhibits acquisition, storage, and maintenance of multi-LOD data. Two methods for linking features across two or more LODs have been developed resulting in an increased consistency of multi-LOD datasets. The first method links matching geometries across multiple LODs, while the second method establishes a 4D data structure in which the LOD is modelled as the fourth (spatial) dimension. It is often believed that the more detailed 3D data the better. However, similarly as in computer graphics, dealing with data at fine LODs comes at a cost: such datasets are harder to obtain, their storage footprint is large, and their usage within a spatial analysis may be slow. Scarce research has been dedicated to investigating whether an increase in the LOD of the data brings a comparably significant increase in benefits when the data is used in a spatial analysis. First, an analysis using real-world multi-LOD data was carried out. Different LODs of spatial data covering the Netherlands was used in a spatial analysis to refine population maps, obtaining different results for each LOD. However, several problems are exposed, revealing that using real data for such investigations is not optimal. The remainder of the research focuses on using procedurally generated data for such experiments. Synthetic data in several different LODs has been generated and employed for four spatial analyses (estimation of the building shadow, envelope area, volume, and solar irradiation). The experiments result in different conclusions. Finer LODs usually bring some improvement to the quality of the spatial analysis, but not always and such may be negligible. The results of the experiments ultimately depend on the spatial analysis that is considered. The varying results between different spatial analyses make each of them unique. Furthermore, the benefit a finer LOD brings to a spatial analysis is not always clear and easily measurable. In short, striving to produce data at finer LODs may please the eye, but this is not always counter-balanced in the benefit it brings to a spatial analysis. A further addition to the equation above is that when realised, 3D city models are unavoidably burdened with acquisition errors. An error propagation analysis was performed by disturbing the procedurally generated datasets with a range of simulated positional errors. Comparisons have been made between the intentionally degraded datasets and their error-free counterparts, thus obtaining the magnitude of uncertainty the positional errors cause in a spatial analysis. Based on these experiments, several findings are discovered, most importantly: 1. How the LODs are realised (which geometric references are used) has a larger influence than the LOD. A coarse LOD produced with a favourable geometric reference may yield better results than a finer LOD realised with an unfavourable reference. 2. Positional errors considerably affect spatial analyses. The effect is comparable across similar LODs. Simpler LODs are sligthly less affected by positional errors, but they may contain a large systematic error. 3. Errors induced in the acquisition process generally cancel out the improvement provided by finer LODs. The main conclusion is that in the considered spatial analyses the positional error has a significantly higher impact than the LOD. As a consequence, it is suggested that it is pointless to acquire geoinformation at a fine LOD if the acquisition method is not accurate, and instead it is advised to focus on the improvement of accuracy of the data. The thesis proposes additional research for future work. For example, since this research focuses specifically on 3D building models, it would be worth extending the research to other urban features such as roads and vegetation. Furthermore, quality control in 3D GIS does not encompass the evaluation of the LOD of data. Hence integration of the LOD in quality standards should be a priority for future work. @en

There has been a great deal of research about errors in geographic information and how they affect spatial analyses. A typical GIS process introduces various types of errors at different stages, and such errors usually propagate into errors in the result of a spatial analysis. However, most studies consider only a single error type thus preventing the understanding of the interaction and relative contributions of different types of errors. We focus on the level of detail (LOD) and positional error, and perform a multiple error propagation analysis combining both types of error. We experiment with three spatial analyses (computing gross volume, envelope area, and solar irradiation of buildings) performed with procedurally generated 3D city models to decouple and demonstrate the magnitude of the two types of error, and to show how they individually and jointly propagate to the output of the employed spatial analysis. The most notable result is that in the considered spatial analyses the positional error has a much higher impact than the LOD. As a consequence, we suggest that it is pointless to acquire geoinformation of a fine LOD if the acquisition method is not accurate, and instead we advise focusing on the accuracy of the data.@en

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.@en

Building datasets (e.g. footprints in OpenStreetMap and 3D city models) are becoming increasingly available worldwide. However, the thematic (attribute) aspect is not always given attention, as many of such datasets are lacking in completeness of attributes. A prominent attribute of buildings is the year of construction, which is useful for some applications, but its availability may be scarce. This paper explores the potential of estimating the year of construction (or age) of buildings from other attributes using random forest regression. The developed method has a two-fold benefit: enriching datasets and quality control (verification of existing attributes). Experiments are carried out on a semantically rich LOD1 dataset of Rotterdam in the Netherlands using 9 attributes. The results are mixed: the accuracy in the estimation of building age depends on the available information used in the regression model. In the best scenario we have achieved predictions with an RMSE of 11 years, but in more realistic situations with limited knowledge about buildings the error is much larger (RMSE = 26 years). Hence the main conclusion of the paper is that inferring building age with 3D city models is possible to a certain extent because it reveals the approximate period of construction, but precise estimations remain a difficult task.@en

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.@en

The remote estimation of a region’s population has for decades been a key application of geographic information science in demography. Most studies have used 2D data (maps, satellite imagery) to estimate population avoiding field surveys and questionnaires. As the availability of semantic 3D city models is constantly increasing, we investigate to what extent they can be used for the same purpose. Based on the assumption that housing space is a proxy for the number of its residents, we use two methods to estimate the population with 3D city models in two directions: (1) disaggregation (areal interpolation) to estimate the population of small administrative entities (e.g. neighbourhoods) from that of larger ones (e.g. municipalities); and (2) a statistical modelling approach to estimate the population of large entities from a sample composed of their smaller ones (e.g. one acquired by a government register). Starting from a complete Dutch census dataset at the neighbourhood level and a 3D model of all 9.9 million buildings in the Netherlands, we compare the population estimates obtained by both methods with the actual population as reported in the census, and use it to evaluate the quality that can be achieved by estimations at different administrative levels. We also analyse how the volume-based estimation enabled by 3D city models fares in comparison to 2D methods using building footprints and floor areas, as well as how it is affected by different levels of semantic detail in a 3D city model. We conclude that 3D city models are useful for estimations of large areas (e.g. for a country), and that the 3D approach has clear advantages over the 2D approach.@en

The level of detail (LOD) of a 3D city model indicates the model's grade and usability. However, there exist multiple valid variants of each LOD. As a consequence, the LOD concept is inconclusive as an instruction for the acquisition of 3D city models. For instance, the top surface of an LOD1 block model may be modelled at the eaves of a building or at its ridge height. Such variants, which we term geometric references, are often overlooked and are usually not documented in the metadata. Furthermore, the influence of a particular geometric reference on the performance of a spatial analysis is not known.In response to this research gap, we investigate a variety of LOD1 and LOD2 geometric references that are commonly employed, and perform numerical experiments to investigate their relative difference when used as input for different spatial analyses. We consider three use cases (estimation of the area of the building envelope, building volume, and shadows cast by buildings), and compute the deviations in a Monte Carlo simulation.The experiments, carried out with procedurally generated models, indicate that two 3D models representing the same building at the same LOD, but modelled according to different geometric references, may yield substantially different results when used in a spatial analysis. The outcome of our experiments also suggests that the geometric reference may have a bigger influence than the LOD, since an LOD1 with a specific geometric reference may yield a more accurate result than when using LOD2 models.

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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.@en