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Optimizing the built environment via simulations of building models hinges on standardizing data acquisition. In this research, we put forward distinct levels of detail for geometry and material inputs, specifically tailored for indoor daylight applications. We primarily focus on understanding the uncertainties arising from imprecise estimations of material optical properties and incomplete geometrical inputs in climate-based indoor daylight simulations. Employing a Monte Carlo approach, we analyzed six office and teaching spaces, creating 20 variations for each by altering geometrical completeness and material accuracy. The technique of excluding non-permanent objects below certain sizes in four graduated steps was used to derive and test the impact of various geometrical levels of detail. Our findings reveal that different levels of geometrical completeness lead to errors ranging from 1.08% to 18.05%. Additionally, a twofold increase in simulation time was noted when geometrical detail was enhanced relative to the most basic model. Errors stemming from imprecise definitions of material optical properties showed a normal distribution. The uncertainty in simulation outcomes showed a linear rise with increasing input material uncertainty, lying between 10% to 30%, depending on space configurations. We observed heightened uncertainty near openings, attributed to window transmittance effects. The research underscores that daylight predictions are markedly more sensitive to transmittance uncertainties than to those in reflectance, regardless of the window-to-floor ratio. These insights may help to guide a more efficient data acquisition process of indoor spaces for daylight simulations., Environmental & Climate Design, Urban Data Science

Historic gardens, regarded as a significant genre of cultural heritage, encapsulate the enduring essence of bygone eras while concurrently transcending temporal boundaries to resonate with the present and future. These gardens provide us vitality and inspiration, holding a collective repository of human memory and serving as a testament to our shared heritage. However, like landscapes, gardens constantly change through natural processes and human interventions. How can we preserve these gardens, though changes are unavoidable? Spatial and visual characteristics are the gardens' essential characteristics, and point-cloud (LiDAR) technologies are powerful tools to reveal and analyze gardens’ spatial-visual relationships and characteristics. Therefore, this paper aims to present a point-cloud-based approach to identifying spatial-visual design principles and making them operational to protect and develop historic gardens. Additionally, several methods have been proposed in this research, including (a) a voxel-based method to transfer points into a solid model for GIS-based computation, (b) a novel method to analyze the field of view (FOV), and (c) a systemic framework to reveal historic gardens’ spatial-visual characteristics based on the voxelized model. Jichang Garden, a historic garden in Wuxi, China, known for its visual design and spatial arrangement, has been selected as a case study to showcase how to apply the methods proposed by this paper. The findings include the design principles for the water body, the arrangement for a route, and the planting strategies of the garden. The conservational strategies have been formed based on the findings, and the appliable potentials and limitations of the methods have also been discussed., Landscape Architecture, Urban Data Science

De 3D BAG bevat automatisch gereconstrueerde LoD2-modellen van alle panden in Nederland, en is voor het eerst gereconstrueerd in het voorjaar van 2021 op basis van AHN3.1 Op basis van AHN4 is een nieuwe versie van de 3D BAG gereconstrueerd, in een samenwerking tussen 3DGI en de onderzoeksgroep 3D Geoinformation (TU Delft). AHN4 is niet alleen van hogere actualiteit, maar heeft ook andere kenmerken dan AHN3. Voor de geactualiseerde versie van 3D BAG hebben we daarom onderzocht hoe beide datasets optimaal gebruikt kunnen worden., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Urban Data Science

Current GIS software offer tools to perform the solar irradiance calculations. However, these computations based their work on data assumptions or generalisations to speed up their processing time. In this work, a method is shown to perform the calculation using very high and very low spatial resolution open datasets. The results show that there too detailed raster data like 50cm horizontal spatial resolution DSM does not improve the calculations compared to lower resolution datasets., Urban Data Science

Noise simulations are an important part of noise studies that investigate the impact of noise sources on the environment. In noise simulation, noise levels at receiver points are calculated based on the noise propagation paths between the receiver and source points. These paths are derived from the height of the terrain. In current calculation approaches implemented in noise simulation software, 3D polylines are used as input to describe the height of the terrain. These 3D polylines are semi-automatically generated to meet the highly demanding computing performance of simulation software. In addition, previous research showed that the reconstruction of appropriate height lines as used in noise simulation is very difficult to automate, if not impossible As a solution, this research investigates how noise propagation paths between receiver and source points can directly be generated from a Triangulate Irregular Network (TIN) without creating the height lines. This would allow us to use the automatically generated TIN as input for noise simulation instead of the height lines. In addition, a TIN enables better control of the quality of the data than height lines do. This study uses the 3D noise modeling guidelines of Common Noise Assessment Methods in Europe (CNOSSOS-EU). Algorithms have been developed and implemented in a prototype to generate and validate the paths between receiver and source points using a TIN that includes the buildings as well as the noise absorption properties of the terrain. The prototype is successfully tested on two scenarios from the Netherlands. Since CNOSSOS-EU guidelines were used, the prototype is applicable to the entire European Union and can be the first step in improving the automation of 3D noise modeling using currently available techniques and data., Urban Data Science

To encourage discussion of the challenges hindering the design and implementation of digital twins, the authors have ranked them based on a systematic literature review combined with an expert survey., Urban Data Science

Symmetry widely exists in nature and man-made shapes, but it is unavoidably distorted during the process of growth, design, digitalization, and reconstruction steps. To enhance symmetry, traditional methods follow the detect-then-symmetrize paradigm, which is sensitive to noise in the detection phase, resulting in ambiguities for the subsequent symmetrization step. In this work, we propose a novel optimization-based framework that jointly detects and optimizes symmetry for 2D shapes represented as polygons. Our method can detect and optimize symmetry using a single objective function. Specifically, we formulate symmetry detection and optimization as a mixed-integer program. Our method first generates a set of candidate symmetric edge pairs, which are then encoded as binary variables in our optimization. The geometry of the shape is expressed as continuous variables, which are then optimized together with the binary variables. The symmetry of the shape is enforced by the designed hard constraints. After the optimization, both the optimal symmetric edge correspondences and the geometry are obtained. Our method simultaneously detects all the symmetric primitive pairs and enhances the symmetry of a model while minimally altering its geometry. We have tested our method on a variety of shapes from designs and vectorizations, and the results have demonstrated its effectiveness., Urban Data Science

Registering point clouds of forest environments is an essential prerequisite for LiDAR applications in precision forestry. State-of-the-art methods for forest point cloud registration require the extraction of individual tree attributes, and they have an efficiency bottleneck when dealing with point clouds of real-world forests with dense trees. We propose an automatic, robust, and efficient method for the registration of forest point clouds. Our approach first locates tree stems from raw point clouds and then matches the stems based on their relative spatial relationship to determine the registration transformation. The algorithm requires no extra individual tree attributes and has quadratic complexity to the number of trees in the environment, allowing it to align point clouds of large forest environments. Extensive experiments on forest terrestrial point clouds have revealed that our method inherits the effectiveness and robustness of the stem-based registration strategy while exceedingly increasing its efficiency. Besides, we introduce a new benchmark dataset that complements the very few existing open datasets for the development and evaluation of registration methods for forest point clouds. The source code of our method and the dataset are available at https://github.com/zexinyang/GlobalMatch., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Urban Data Science

Continuous implicit representations can flexibly describe complex 3D geometry and offer excellent potential for 3D point cloud analysis. However, it remains challenging for existing point-based deep learning architectures to leverage the implicit representations due to the discrepancy in data structures between implicit fields and point clouds. In this work, we propose a new point cloud representation by integrating the 3D Cartesian coordinates with the intrinsic geometric information encapsulated in its implicit field. Specifically, we parameterize the continuous unsigned distance field around each point into a low-dimensional feature vector that captures the local geometry. Then we concatenate the 3D Cartesian coordinates of each point with its encoded implicit feature vector as the network input. The proposed method can be plugged into an existing network architecture as a module without trainable weights. We also introduce a novel local canonicalization approach to ensure the transformation-invariance of encoded implicit features. With its local mechanism, our implicit feature encoding module can be applied to not only point clouds of single objects but also those of complex real-world scenes. We have validated the effectiveness of our approach using five well-known point-based deep networks (i.e., PointNet, SuperPoint Graph, RandLA-Net, CurveNet, and Point Structuring Net) on object-level classification and scene-level semantic segmentation tasks. Extensive experiments on both synthetic and real-world datasets have demonstrated the effectiveness of the proposed point representation., Urban Data Science

Many challenges to operate digital twins remain, hindering their design and implementation, and are rarely discussed. Furthermore, issues of social and legal nature are often overlooked. We identify the challenges of operating digital twins in the urban context through a bifurcated and multi-dimensional approach: a systematic literature review and an expert survey. The review organises the identified challenges across technical and non-technical dimensions. As the topic is novel, the corpus is rather small and lacking the contextualisation of challenges. Thus, we complement it with a survey based on the Delphi method, involving a diverse panel of domain experts covering academia, industry and government organisations. Combining the results, we identify 14 technical and 9 non-technical challenges and map them to phases of the digital twin's life cycle. The most severe challenges appear to be related to interoperability (e.g. disparate semantic standards) and practical value (e.g. lack of business models)., Urban Data Science

This document provides a description of the project “Computing volumes and surface areas including party walls for the 3DBAG dataset” which has been carried out between the 3D Geoinformation group at TU Del6, 3DGI, and RVO in the timeframe between November 2022 and October 2023. The goal of this project is to derive parameters from the 3DBAG that are relevant for energy consumption estimation, i.e. the enclosed volume of each building, as well as the party wall areas, the exterior wall areas, the ground floor areas and the roof areas. As the detection of the party wall (i.e. the portion of the building shell that is shared between two buildings (BAG-panden)) is the most complex task to solve, specifically for a large data set, the main goal of the project is to define, evaluate and implement a methodology to compute the area extents of party walls between adjacent buildings from the 3DBAG data set. The 3DBAG dataset was first released in March 2021. A first revised version was released in September 2021 which we used for our analysis carried out during the first part of this project. The latest (5th) version has been released in October 2023 based on which we generated the final data for this project. In this last version AHN4 has been incorporated. 3DBAG is a country-wide dataset containing all buildings in the Netherlands, modelled in multiple LoDs, and based on the international standard CityGML. According to CityGML, a building can be modelled as a single-part unique object, or as an aggregation of building parts, each one having its own geometry. Additionally, each building is a geographical feature that can have several aTributes (e.g. year of construction, number of storeys, etc.) and different geometries representing each one a specific Level of Detail (LoD). A graphical overview of the different LoDs according to CityGML v. 2.0 is given in Figure 1. In particular, the LoD2 allows differentiating between different thematic, Urban Data Science

The basic concept of a Digital Twin (DT) is a realistic digital representation of a physical thing with two-way flow of information from the physical to the model and back: one way is a refinement of the digital representation, back is the triggering of real impacts on the depicted reality. This concept was introduced by the manufacturing community to improve product life-cycle. It has extended to the built environment and underpins areas ranging from urban administration to telecommunications. Locationenabled Digital Twins are investigated at city and national levels motivated by cost reduction, efficiency, decision-making and innovation, and particularly to contribute to local and national Net Zero initiatives [Ellul et al. 2022]., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Urban Data Science

This paper focuses on GIS-based visibility analysis to explore landscape architecture com-positions as a means to understand visual-spatial characteristics and identify related design principles. More specifically, the paper elaborates a practical method to employ high-resolution data acquired by terrestrial LiDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging) for this pur-pose. Though LiDAR provides a powerful means to digitally capture the real-world, methods like GIS-based visual landscape research that utilize viewshed analysis ideally require a continuous Digital Landscape Model conduct visibility computation. Therefore, one of the obstacles before the visual analysis is to process the points into surface or solid models. Voxel-based algorithms are powerful means to process LiDAR data. There are many applications known of voxel-based visibility analysis but requires often specialist software that is hard to handle or unavailable to landscape architects in practice. This paper showcases an attempt to use standard software for voxel-based visibility analysis. It presents a practical method for applications in landscape architecture analysis. Jichang Garden (Wuxi, China) is used as an example. The historical garden is an evocative example of a landscape architecture compo-sition that displays skilful applications of spatial-visual design principles and therefore worthy of ana-lyse., Landscape Architecture, Urban Data Science

We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missing. Based on the observation that urban buildings typically consist of planar roofs connected with vertical walls to the ground, we propose an approach to infer the vertical walls directly from the data. With the planar segments of both roofs and walls, we hypothesize the faces of the building surface, and the final model is obtained by using an extended hypothesis-and-selection-based polygonal surface reconstruction framework. Specifically, we introduce a new energy term to encourage roof preferences and two additional hard constraints into the optimization step to ensure correct topology and enhance detail recovery. Experiments on various large-scale airborne LiDAR point clouds have demonstrated that the method is superior to the state-of-the-art methods in terms of reconstruction accuracy and robustness. In addition, we have generated a new dataset with our method consisting of the point clouds and 3D models of 20k real-world buildings. We believe this dataset can stimulate research in urban reconstruction from airborne LiDAR point clouds and the use of 3D city models in urban applications, Urban Data Science

In this chapter, we start from the typical concepts from Geographic Information System (GIS): data representation, acquisition, querying and analysis. We follow with the transition from 2 to 3D GIS and describe open standards such as CityGML and CityJSON and recent advances on 3D geospatial simulations, computing and real-time GIS and Internet of Things (IoT). Then we discuss the discrepancies in information management and modelling with respect to Building Information Modelling (BIM) and the related open standard, Industry Foundation Classes (IFC). We highlight the difference between Cartesian engineering coordinate systems and geospatial coordinate reference systems, contrast the procedural geometry definitions of IFC with the explicit geometries of GIS and look at implementation mechanisms such as boundary representations and polyhedral surface models and describe the semantic Level of Detail used in CityGML. The section that follows describes relevant processes supporting integration such as georeferencing, conversion of formats using semantic and geometric approaches and linking of heterogeneous information. We also highlight interoperability challenges that stem from consistency and validity of data, by interpreting the results of a recent benchmark on interoperability of the most common involved data formats (CityGML and IFC). We close with a conclusion and perspectives on the future with case studies on geo-enabled building permit checking and geospatial artificial intelligence and machine learning., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Urban Data Science

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., Urban Data Science

To support building permit issuing with automatic digital tools, the reuse of models produced by designers would make the process quicker and more objective. However, current studies and pilots often leave a gap with respect to the models as actually provided by architects, having varying quality and content. In this study, rather than taking a top down approach, we started from the available data and made the necessary inferences, which gave the opportunity to tackle basic and common issues often preventing smooth automatic processing. Specific characteristics of the IFC models were outlined and a tool was developed to extract the necessary information from them to check representative regulations. While the case study is specific in location, regulations and input models, the type of issues encountered are a generally applicable example for automated code compliance checking. This represents a solid base for future works towards the automation of building permits issuing., Urban Data Science

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., Urban Data Science

Municipalities invest a lot of time and person-hours into manual building permit checks. With the increase in computational power and the use of Building Information Models (BIM) in the building design life cycle, several municipalities are investing in automating these checks using BIM and geo-data sets. However, few examples exist of tools effectively using geo-information with BIM. In order to address this gap, a project was developed with the municipality of Rotterdam (NL). In a previous phase, a tool was implemented, able to analyse the BIM data to extract the needed information for a few representative regulations. In order to extend and improve the previously developed tool, a web-based interface is now implemented and geo-data sets are integrated to the process allowing more powerful GeoBIM analysis. Three checks using both BIM and GIS data were implemented and tested: (i) The parcel limit check evaluates if the building's footprint derived from BIM falls within the parcel limit provided from the municipalities' parcel data sets. (ii) The height check evaluates the maximum building's relative height to the road's height. Finally, (iii) the road overhang check detects neighbouring roads to the parcel and evaluates the admissible overhang over that road. This paper presents these developments, including the type of input data that is needed for the checks, the tools for the three new GeoBIM checks (parcel limit check, height check, road overhang check) and the implementation in the web-based tool., Urban Data Science

Feedforward fully convolutional neural networks currently dominate in semantic segmentation of 3D point clouds. Despite their great success, they suffer from the loss of local information at low-level layers, posing significant challenges to accurate scene segmentation and precise object boundary delineation. Prior works either address this issue by post-processing or jointly learn object boundaries to implicitly improve feature encoding of the networks. These approaches often require additional modules which are difficult to integrate into the original architecture. To improve the segmentation near object boundaries, we propose a boundary-aware feature propagation mechanism. This mechanism is achieved by exploiting a multitask learning framework that aims to explicitly guide the boundaries to their original locations. With one shared encoder, our network outputs (i) boundary localization, (ii) prediction of directions pointing to the object's interior, and (iii) semantic segmentation, in three parallel streams. The predicted boundaries and directions are fused to propagate the learned features to refine the segmentation. We conduct extensive experiments on the S3DIS and SensatUrban datasets against various baseline methods, demonstrating that our proposed approach yields consistent improvements by reducing boundary errors. Our code is available at https://github.com/shenglandu/PushBoundary., This work was supported by the 3D Urban Understanding Lab funded by the TU Delft AI Initiative. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Urban Data Science, Intelligent Vehicles

3D city models are frequently used to acquire and store energy-related information of buildings for energy applications. In this context, CityGML is the most common data model, and the Energy ADE, one of its most complex extensions, provides a systematic way of storing detailed energy-related data in XML format. Contrarily, even though CityGML's JSON-based encoding, CityJSON, has an extension mechanism, an energy-related CityJSON Extension is missing. This paper, therefore, presents the first results of the development of a CityJSON Energy Extension and space heating demand calculation is utilized as the use case. The simplified version of the Energy ADE, called the Energy ADE KIT profile, is used to create a semi-direct translation to the CityJSON Energy Extension. This Extension is then validated through the official validator of CityJSON and the use case, and improvements are made considering the validation results. The space heating demand is calculated according to the Dutch standard NTA 8800 for a subset of Rijssen-Holten in the Netherlands although the solar gains calculation requires further review. The results show that the final CityJSON Energy Extension provides full support for space heating demand calculations based on the NTA 8800 and eliminates the deep hierarchical structure of the Energy ADE. A comparison on CityJSON file sizes shows a 25.2 MB increase after the required input data is stored in a CityJSON + Energy Extension file, which is not significant considering the high amount of data stored in the file. Overall, this paper shows that the CityJSON Energy Extension could provide an easy-to-use alternative to the CityGML Energy ADE., Urban Data Science

Digital Twins are realistic digital representation of physical objects and are differentiated from traditional models by the live connection between the digital and the physical worlds, often enabled by sensors. They provide insights into the physical world for decision makers, for example via simulation, and can be used to directly alter the physical world without manual intervention. While they have their origins in manufacturing, they are increasingly being used within the built environment, by both public and private sectors. Increasingly city-wide and National Digital Twins are also being considered, to underpin local, municipal and central government decision making. For these emerging Digital Twins, location data such as that provided by National Mapping and Cadastral Agencies (NMCAs) has the potential to underpin Digital Twin modelling. It thus becomes important for NMCAs to better understand Digital Twins in order to determine whether current data offerings can meet this new demand and how best to support the various activities. As a first stage investigation under the auspices of EuroSDR, this paper explores challenges and opportunities for NMCAs and others working in the location sector, presenting the result of an international survey and workshop on these topics. We conclude that there is significant overlap with existing challenges within the geospatial community and those required to better support Digital Twins-e.g. interoperability and data management and governance. Additionally, the opportunity for a broader understanding and uptake of location data offered by Digital Twins should not be ignored., Urban Data Science

This document introduces the process for the creation of a testbed for energy applications based on a semantic 3D city model for the municipality of Rijssen-Holten in The Netherlands. The creation of this dataset requires the consolidation from multiple data sources as well as a lot of manual work so the authors can warranty as much as possible the quality of the dataset so in can be used in several use cases. The data is stored following the OGC standard CityGML v2.0 and contain the geometrical and semantical information of CityObjects from the thematic modules Building, Vegetation and Relief. This data set consolidates the open weather data from the closest weather station to the study area located in Heino in the Netherlands. We discuss the decisions taken during the manual data collection process and we present some use cases that have already consume the dataset at the time of writing this document., Urban Data Science

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., Urban Data Science

In the last 15 years semantic 3D city models have seen a steady growth in terms of creation and adoption. Many cities world-wide have now at least one city model which can be used for several applications. Energy- and sustainability-related topics are among those that have experienced a noteworthy increase of interest from the Geomatics community. 3D city models have become a steady component of Urban Energy Modelling, in which bottom-up approaches are developed to assess, for example, the energy efficiency of the building stock and to explore different scenarios of building refurbishment. Within this context, this paper focuses on investigating how much party walls can contribute to the energy demand estimation of a building. For this reason, two approaches to compute party walls are described and compared. The nature and the magnitude of their differences, as well as their possible impact on downstream applications, are considered in order to shed light on whether discrepancies in the amount of computed party wall area might lead to significant differences in terms energy demand of the residential building stock. The case study area is located in the Netherlands and encompasses the municipality of Rijssen-Holten., Urban Data Science

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., Urban Data Science

3D-representaties van onze leefomgeving zijn belangrijk in toepassingen die helpen bij de planning, de inrichting en het beheer van de openbare ruimte. Met 3D-modellen kunnen simulaties worden uitgevoerd voor bijvoorbeeld geluid, energie, luchtkwaliteit, windcomfort, zicht en wateroverlast. Om deze simulaties te bedienen met dezelfde 3D-gegevens, zijn standaarden essentieel. Voor bruikbaarheid in de praktijk moet een standaard voor 3D-data zowel specifiek als generiek zijn, eenvoudig gebruik van 3D-data mogelijk maken, en niet te grote bestanden opleveren. Dat is de motivatie geweest om CityJSON te ontwikkelen, een JSON-encoding (JavaScript Object Notation) van de OGC-standaard CityGML., Urban Data Science

De digital twin wordt gezien als een veelbelovende technologie om grote omgevingsvraagstukken op te lossen, zoals de energieransitie en huisvesting. Maar hoe zorgen we ervoor dat omplementaties niet beperkt blijven tot afzonderlijke - veelal technische - deeloplossingen? Volgens Jantien Stoter kunnen antwoorden komen uit het geo-datadomein dat zich al decennialang bezighoudt met het modelleren van de werkelijkheid in ruimtelijke datarepresentaties ten behoeve van analyses en simulaties., Urban Data Science

3D city models are playing a growing role worldwide as sources of integrated information upon which different urban applications are developed. In the context of urban planning and design, semantic 3D city models can provide plenty of qualitative and quantitative information about the urban context and of the area(s) to be transformed. This paper takes inspiration and continues a work recently published in which several design parameters and Key Performance Indicators are computed from a semantic 3D city model, and later used in a GIS-supported urban design process to develop a new area. As many of such parameters are derived from the gross volume of the building stock, this paper investigates whether and to which extent different building stock models might affect the estimation of the gross volume. The study is carried out in anticipation of the upcoming LoD2-based, country-wide model of the Netherlands that is being finalised by our team. At the same time, the paper investigates whether and which information can be obtained regarding the quality of the LoD2 model from a comparison with the LoD1 one, with a focus on volume calculation., Urban Data Science

De term Digital Twin wordt op allerlei manieren gebruikt sinds dit concept een aantal jaren geleden haar intrede deed in het geodomein als veelbelovende technologie om grote maatschappelijke opgaven en omgevingsvraagstukken op te lossen. Hoewel er consensus bestaat over de basisfunctionaliteiten van een Digital Twin, is het risico van de diversiteit aan definities dat alles en niets hieronder valt. Hierdoor kunnen implementaties beperkt blijven tot afzonderlijke – veelal technische – onderdelen, en wordt het beloofde einddoel van een fundamentele oplossing voor maatschappelijke en omgevingsvraagstukken nooit behaald. In dit artikel reflecteren wij op het concept Digital Twin binnen de geo-informatie. We beschrijven de potenties en uitdagingen om Digital Twin in al haar facetten te implementeren in de praktijk, daarbij gebruikmakend van bestaande ervaringen en kennis in het geodomein., Urban Data Science

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., Urban Data Science

The concept of the digital twin has been gaining significant momentum in the geospatial domain since 2016. Although there is some consensus on the basic features of a digital twin, some critical reflection is still necessary to make the concept tangible. Only then can the digital twin be implemented as a technical solution that scales to real-world problems rather than being an abstract vision for partial solutions. In this article, the authors reflect on the practical digital twin-related challenges in the geospatial domain., Urban Data Science

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., Urban Data Science, Urbanism

Overheden moeten kunnen beoordelen of de geluidsbelasting op bijvoorbeeld een woonwijk binnen wettelijke limieten valt. Daarvoor moeten geluidsniveaus worden gesimuleerd. Het Kadaster, RIVM, RWS, IPO en TU Delft (3D Geoinformation) zijn in 2017 begonnen met een project om vanuit bestaande gegevens 3D-inputdata voor geluidsstudies te genereren, aansluitend op onze andere 3D-projecten (zoals bijvoorbeeld beschreven in de vorige Geo-Info). De algoritmes waren vorig jaar goed genoeg voor een landsdekkende uitrol. Sinds februari 2021 is dit 3D-omgevingsmodel voor Geluid als open data via PDOK beschikbaar., Urban Data Science

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., Urban Data Science

3D cartographic visualization of a continuous time-dependent phenomenon is not an easy task. The focus of this research is motivated by the struggle to visualize such a phenomenon. Based on the current state of the art, we implemented new visualization methods to visualize continuous time-dependent phenomena. All visualizations are based on the use case of road-traffic-generated noise in outdoor urban areas. These visualizations utilize the third dimension of the map scene. The first two methods focus on the variations of the noise in the vertical dimension (i.e. height). The third method is based on the idea of space–time cube and therefore utilizes the time variable as the third dimension. For demonstration purposes, all methods were implemented in an online application. Furthermore, user testing of those applications was conducted. This paper thus describes design, implementation and user evaluation of newly proposed methods for third dimension visualization., Urban Data Science

This article examines how GIS can be used as a heuristic tool to reconstruct spatial–temporal events from narratives in order to examine whether a scenario is conceivable within the narrative world. The narrative about Paul's escape from Berea (Acts 17:14–15) is used as a case study. Several interpretive issues related to spatial and temporal questions surround these texts. In the case study, three methods are applied: (a) least-cost path analysis on elevation data to construct journeys and travel times for Roman roads; (b) network analysis to find seafaring routes valid for ancient times; and (c) the integration of spatial and temporal data in a space-time cube. Our main finding is that the method yields insights into the spatial–temporal dynamics of the narrative. This helps a modern reader to better understand the narrative conceivability of a story in the mind of a first-century reader., Urban Data Science

Three-dimensional city models are essential to assess the impact that environmental factors will have on citizens, because they are the input to several simulation and prediction software. Examples of such environmental factors are noise (Stoter et al., 2008), wind (Garcı́a-Sánchez et al., 2014), air pollution (Ujang et al., 2013), and temperature (Hsieh et al., 2011; Lee et al., 2013). However, those 3D models, which typically contain buildings and other man-made objects such as roads, overpasses, bridges, and trees, are in practice complex to obtain, and it is very time-consuming and tedious to reconstruct them manually. The software 3dfier addresses this issue by automating the 3D reconstruction process. It takes 2D geographical datasets (e.g., topographic datasets) that consist of polygons and “3dfies” them (as in “making them three-dimensional”). The elevation is obtained from an aerial point cloud dataset, and the semantics of the polygons is used to perform the lifting to the third dimension, so that it is realistic. The resulting 3D dataset is semantically decomposed/labelled based on the input polygons, and together they form one(many) surface(s) that aim(s) to be error-free: no self-intersections, no gaps, etc. Several output formats are supported (including the international standards), and the 3D city models are optimised for use in different software., Urban Data Science

Industry Foundation Classes (IFC) is a complete, wide and complex open standard data model to represent Building Information Models. Big efforts are being made by the standardization organization buildingSMART, to develop and maintain this standard in collaboration with researchers, companies and institutions. However, when trying to use IFC models from practice for automatic analysis, some issues emerge, as a consequence of a misalignment between what is prescribed by, or available in, the standard with the data sets that are produced in practice. In this study, a sample of models produced by practitioners for aims different from their explicit use within automatic processing tools is inspected and analyzed. The aim is to find common patterns in data set from practice and their possible discrepancies with the standard, in order to find ways to address such discrepancies in a next step. In particular, it is noticeable that the overall quality of the models requires specific additional care by the modellers before relying on them for automatic analysis, and a high level of variability is present concerning the storage of some relevant information (such as georeferencing)., Urban Data Science

Industry Foundation Classes (IFC), the buildingSMART open standard for BIM, is underused with respect to its promising potential, since, according to the experience of practitioners and researchers working with BIM, issues in the standard’s implementation and use prevent its effective use. 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. Interestingly, different IFC software programs with the same standardized data sets yield inconsistent results, with few detectable common patterns, and significant issues are found in their support of the standard, probably due to the very high complexity of the standard data model. A companion article (Part II) describes the results of the benchmark related to CityGML, the counterpart of IFC within geoinformation., Urban Data Science

The 3D BAG v. 2.0 dataset has been recently released: it is a country-wide dataset containing all buildings in the Netherlands, modelled in multiple LoDs (LoD1.2, LoD1.3 and LoD2.2). In particular, the LoD2.2 allows differentiating between different thematic surfaces composing the building envelope. This paper describes the first steps to test and use the 3D BAG 2.0 to perform energy simulations and characterise the energy performance of the building stock. Two well-known energy simulation software packages have been tested: SimStadt and CitySim Pro. Particular care has been paid to generate a suitable, valid CityGML test dataset, located in the municipality of Rijssen-Holten in the central-eastern part of the Netherlands, that has been then used to test the energy simulation tools. Results from the simulation tools have been then stored into the 3D City Database, additionally extended to deal with the CityGML Energy ADE. The whole workflow has been checked in order to guarantee a lossless dataflow. The paper reports on the proposed workflow, the issues encountered, some solutions implemented, and what the next steps will be., Urban Data Science