The widespread use of three-dimensional (3D) city data plays a significant role in various applications, such as mixed reality, infrastructure facility management, solar potential analysis, navigation, and so on. Ensuring high spatial and semantic quality in these endeavours is crucial to gathering proper results. Ensuring quality means verifying that the data adheres to relevant standards. Although these relevant standards are openly published, there are issues with the names of interoperability and reusability in academic studies and software development efforts. In this study, these issues are addressed using semantic web technologies. Most 3D city models (3DCMs) are treated as knowledge graphs (KG) with this approach. The main contribution of the study is a web-based interoperable tool for validation of CityGML Level of Detail 2 (LOD2) 3DCMs, which is compatible with relevant standards. Besides, an open-source 3DCM-to-KG converter and an open validation ontology are published as by-products while accomplishing the main goal. By virtue of the KG approach, the 3DCM KG becomes capable of carrying its own validation constraints, which come from the validation ontology. With these efforts, this study provides a practical, interoperable solution to improve the quality and usability of 3DCMs and validation plans, fostering consistency across applications while aligning with established standards in the field.

Urban morphological analytics on buildings is informative for sustainable development. 3D building massing features, such as courtyards and setbacks, reflect spatial organizations and circulations, while influence daylight access, ventilation, and shading. However, existing 3D GIS methods usually overlook such 3D massing features, further obscure morphological analytics and environmental assessment. This article proposes MorphCut, an efficient convex decomposition method that segments 3D shapes into mass-aligned parts. MorphCut leverages key morphological properties—planarity, regularity, and Gestalt laws—after a topological preprocessing step to enable mass-aware decomposition. Experiments on representative samples, ranging from small houses to complex skyscrapers, showed that MorphCut outperformed four baseline methods in (i) balancing convexity and compactness, (ii) aligning decomposed parts with building masses, and (iii) preserving geometric fidelity (average deviation: 0.25 m). An urban-scale validation on datasets from Delft and Hong Kong, comprising over 30,000 buildings across 18.3 km², demonstrated MorphCut’s robustness, scalability, and generalizability. MorphCut successfully decomposed 98% of buildings in low-rise regions (+78% over the second-best method) and 93% in high-rise areas (+2%), completing processing in 13 hours (3 hours faster). These results position MorphCut as a foundational 3D GIS tool for large-scale, mass-aware morphological analysis, with implications for digital twins, sustainable planning, and environmental modeling.

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 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.

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.

While error propagation in GIS is a topic that has received a lot of attention, it has not been researched with 3D GIS data. We extend error propagation to 3D city models using a Monte Carlo simulation on a use case of annual solar irradiation estimation of building rooftops for assessing the efficiency of installing solar panels. Besides investigating the extension of the theory of error propagation in GIS from 2D to 3D, this paper presents the following contributions. We (1) introduce varying XY/Z accuracy levels of the geometry to reflect actual acquisition outcomes; (2) run experiments on multiple accuracy classes (121 in total); (3) implement an uncertainty engine for simulating acquisition positional errors to procedurally modelled (synthetic) buildings; (4) perform the uncertainty propagation analysis on multiple levels of detail (LODs); and (5) implement Solar3Dcity – a CityGML-compliant software for estimating the solar irradiation of roofs, which we use in our experiments. The results show that in the case of the city of Delft in the Netherlands, a 0.3/0.6 m positional uncertainty yields an error of 68 kWh/m2/year (10%) in solar irradiation estimation. Furthermore, the results indicate that the planar and vertical uncertainties have a different influence on the estimations, and that the results are comparable between LODs. In the experiments we use procedural models, implying that analyses are carried out in a controlled environment where results can be validated. Our uncertainty propagation method and the framework are applicable to other 3D GIS operations and/or use cases. We released Solar3Dcity as open-source software to support related research efforts in the future.

One solution to the integration of additional characteristics, e.g. time and scale, into geographic information system (GIS) datasets is to model them as extra geometric dimensions perpendicular to the spatial ones, creating a higher-dimensional model. Previous work has been mostly limited to higher-dimensional rasters and hierarchies of trees, which grow exponentially with the dimension. As representations with limited topological relationships quickly become intractable in higher dimensions, a topological vector approach seems most suitable for this purpose, requiring the use of higher-dimensional topological data structures. We therefore present in this paper an evaluation and classification of the possible data structures for an nD GIS, including how they can be implemented to support real-world data aspects, such as holes, disconnected components and attributes, as well as practical issues that affect their feasibility, like the availability of algorithms, libraries and software.

One solution to the integration of additional characteristics, for example, time and scale, into GIS data sets is to model them as extra geometric dimensions perpendicular to the spatial ones, creating a higher-dimensional model. While this approach has been previously described and advocated, it is scarcely used in practice because of a lack of high-level construction algorithms and accompanying implementations. We present in this paper a dimension-independent extrusion algorithm permitting us to construct from any (n–1)-dimensional linear cell complex represented as a generalised map, an n-dimensional one by assigning to each (n–1)-cell one or more intervals where it exists along the nth dimension. We have implemented the algorithm in C++11 using CGAL, made the source code publicly available and tested it in experiments using real-world 2D GIS data sets which were extruded to construct up to 5D models.

Building patterns are important features that should be preserved in the map generalization process. However, the patterns are not explicitly accessible to automated systems. This paper proposes a framework and several algorithms that automatically recognize building patterns from topographic data, with a focus on collinear and curvilinear alignments. For both patterns two algorithms are developed, which are able to recognize alignment-of-center and alignment-of-side patterns. The presented approach integrates aspects of computational geometry, graph-theoretic concepts and theories of visual perception. Although the individual algorithms for collinear and curvilinear patterns show great potential for each type of the patterns, the recognized patterns are neither complete nor of enough good quality. We therefore advocate the use of a multi-algorithm paradigm, where a mechanism is proposed to combine results from different algorithms to improve the recognition quality. The potential of our method is demonstrated by an application of the framework to several real topographic datasets. The quality of the recognition results are validated in an expert survey.

This article describes a research project that realised a national standard for 3D geo-information. The standard was developed as part of a pilot in which more than 65 private, public and scientific organisations collaborated to analyse and push 3D developments in the Netherlands (run between March 2010 and June 2011). The 3D standard was established through several steps. First, a comparison between the existing 3D computer-aided design and GIS standards was carried out that selected the Open Geospatial Consortium (OGC) standard CityGML as the optimal 3D standard to align to. Second, the equivalent concepts in CityGML and the existing national standard for large-scale topography (Information Model Geography [IMGeo]) were identified. Third, IMGeo was extended to 3D following the principles of CityGML Application Domain Extensions. The model was tested by applying it to real data. Based on the experiences of this pilot, this article proposes a framework of guidelines and principles for extending CityGML for national purposes, deduced from the modelling experiences. This is a unique contribution since experiences on extending CityGML are new and not well described in the OGC CityGML specifications. Finally, this article presents the change requests (CRs) which have been submitted to OGC to make the CityGML standard more suited for integration with existing 2D topographic information models. The CRs were formulated based on experiences from developing this nationwide 3D standard.

Evaluation is a key step to examine the quality of generalized maps with respect to map requirements. Map generalization facilitates the recognition of pattern generating processes by preserving and highlighting the patterns at smaller scales. This article focuses specifically on the evaluation of building patterns in topographic maps that are generalized from large to mid scales. Currently, there is a lack of knowledge and functionality on automatically evaluating how these patterns are generalized. The issues of the evaluation range from missing formal map requirements on building alignments to missing automated evaluation techniques. This article firstly analyses the requirements (constraints) related to the generalization of building alignments. Then, it focuses on three more specific constraints, i.e. on existence, orientation of alignments and spatial distribution of composing buildings. Later, a three-step approach is proposed to (1) recognize and (2) match alignments from source and generalized datasets and (3) evaluate building alignments in generalized datasets. Besides, many-to-many and partial matching between initial and target alignments is a side effect of generalization, which reduces the reliability of the evaluation results. This article introduces a confidence indicator to document the reliability and to inform intended users (e.g. cartographers) and/or systems about the reliability of evaluation decisions. The effectiveness of our approach is demonstrated by evaluating the alignments in both interactively (manually) generalized maps and automated generalized maps. Finally, we discuss how our approach can be used to control automated generalization and identify further improvements.

Thematic content in the form of geodata is becoming increasingly available on the web. However, adequate base map information to support appropriate communication of the thematic content is not available in many cases. This base map information might be served through topographic databases available on the web and optimized by means of automated generalization. This article describes an approach based on user profiles, which formally captures the user requirements (preferences) towards the base map and deploys those profiles in a web-based architecture to generate on-demand maps. Those user profiles, which may differ per user, drive the generalization process and produce base maps on demand by taking into account the user requirements as well as the thematic content. The research in this article specifically focuses on the technological environment that generates on-demand base maps incorporating four basic concepts in the user profile: (1) topology awareness between the base map and the thematic content, (2) user-specific base map information at a non-uniform scale to improve the communication of the thematic content, (3) the map specification and (4) inheritance of user profiles. Both existing and new techniques are explored to realize the environment. The approach is evaluated by applying it to a project in the Netherlands dedicated to disseminating physical planning maps through the web.

The increasing complexity and flexibility of modern land use requires that cadastres need to manage information on the third and temporal (fourth) dimension. This article considers the registration of legal space of utility networks in cadastre in this 3D + time (=4D) context. A requirement analysis in three countries that have methods to register utility networks complying with their legal, organizational and technical structure (Turkey, the Netherlands and Queensland, Australia) is the basis for three alternatives for 4D cadastre to register utility networks. The three alternatives are analysed with respect to legal, organizational and technical cadastral requirements. This article presents a case study and a prototype from the Netherlands. In this country by law utilities are considered to be real estate objects with obligatory registration of ownership and geometry. This study shows that the 3D space and separate temporal attributes approach (state-based model) is a very promising solution to maintain temporal changes of utility networks and that this approach is to be preferred above the current practice, where the 3D and temporal aspects are not considered when registering a network.

National mapping agencies maintain topographic data sets at different scales. Keeping the data sets consistent, for example by means of automated update propagation, requires formal knowledge on how the different data sets relate to each other. This article presents a multi-scale information model that, first, integrates the data states at the different scales and, second, formalises semantics on scale transitions. This is expressed using the Unified Modelling Language (UML) class diagrams, complemented with Object Constraint Language (OCL). Based on a requirement analysis using the needs of the Netherlands' Kadaster as case study, this article examines several modelling alternatives and selects the optimal modelling approach for a multi-scale information model for topography. The model is evaluated through a prototype database implementation. The results show that UML/OCL provides an appropriate formalism to model rich semantics on both multi-scale data content and scale transitions, which can be used for guarding consistency based on automated generalisation of updates. Further research is required to express generalisation specifications that are currently not formalised and that are only available in software code or as cartographers' knowledge.

Noise mapping is the process of determining and visualizing noise impact on the environment in order to support environmental policies. Currently most noise impact studies are based on a 2D approach. The 3D output of noise simulation software is processed and visualized in 2D and combined with 2D topographical and other data, such as population distribution, to quantify the effects. The research described in this paper aims at improving visualization and assessment of noise impact on the environment by generating a 3D noise map in cases where 3D effects are relevant. Based on the specific demand, an approach is presented to generate a 3D noise map as a basis for noise impact studies. The proposed concept is proofed by applying it to a sample noise impact study. From experiences with the sample, it can be concluded that the 3D noise map offers significant insight in situations where 3D noise effects are relevant, i.e. in urban areas. Here, current 2D noise maps have limitations. In addition, more accurate assessment of noise impact is possible in particular when different floors of a building close to the noise source and/or behind noise barriers are considered. This paper also elaborates on accuracy aspects in all phases of noise modelling, including a presentation of initial experiments of 3D noise interpolation.

In this paper, we present a new conceptual model for a full 3D cadastral registration system. Two important components are: (1) the ‘surface parcel partition’ based on a detailed elevation model and (2) the volume parcel and its representation. Technological solutions for both parts are not yet available in commercial Geo‐ICT software, and therefore solutions have been investigated, designed and developed (in a Geo‐DBMS environment). A number of countries in the world do already have legislation allowing the registration of volume parcels, sometimes even including detailed regulations for 3D survey plans. However, until now, these have not yet been integrated in the cadastral information system. A 3D case from Queensland, Australia is presented, and a prototype is realized based on an integrated 3D cadastral information system: elevation‐model‐based surface parcels complemented with volume parcels.