3D City Models Research Articles

An automated system for 2D building detection from UAV-based geospatial datasets

The focus of this manuscript is on integrating optical images and laser point clouds carried on low-cost UAVs to create an automated system capable of generating urban city models. After pre-processing both datasets, we co-registered both datasets using the DLT transformation model. We estimated structure heights from the LiDAR dataset through a progressive morphological filter followed by removing bare ground. Unsupervised and supervised image classification techniques were applied to a six-band image created from the optical and LiDAR datasets. After finding building footprints, we traced their edges, outlined their borderlines, and identified their geometric boundaries through several image processing and rule-based feature identification algorithms. Comparison between manually digitized and automatically extracted buildings showed a detection rate of about 92.3 % with an average of 7.4 % falsely identified areas with the six-band image in contrast to classifying only the RGB image that detected about 63.2 % of the building pixels with 25.3 % pixels incorrectly identified. Moreover, our building detection rate with the 6-band image was superior to that attained by performing traditional image segmentation for only the LiDAR DEM. Shifts in the horizontal coordinates between corner points identified by a human operator and those detected by the proposed system were in the range of 10–15 cm. This is an improvement over traditional satellite and manned-aerial large mapping systems that have lower accuracies due to sensor limitations and platform altitude. These findings demonstrate the benefits of fusing multiple UAV remote sensing datasets over utilizing a single dataset for urban area mapping and 3D city modeling.

Reviewing Open Data Semantic 3D City Models to Develop Novel 3D Reconstruction Methods

Abstract. Structured semantic 3D city models are pivotal in creating urban 3D digital twins. The wide adoption of such models has been primarily enabled by robust, model-based, and automatic 3D reconstruction methods. However, these methods impose requirements on the reconstruction, mainly restricting the solution space to several model types and relying on accurate 2D footprints. Recent research shows that deep-learning-based methods promise highly generic solution space and are footprint-free. Yet, the current training and test datasets are limited, hindering the methods’ development. In this work, we analyze the ubiquity of already existing, open 3D city model datasets and their potential to serve as a large-scale training and test set for 3D reconstruction, where 27 potential dataset collections have been identified. Our review shows that more than 215 million building models are readily available. We firmly believe that this review will facilitate further research on robust automatic 3D city model reconstruction and serve as a reference for benchmarking 3D city models.

A Geodatabase Design for the Development of a Digital Twin for Urban Environments: A Case Study from Turin, Italy

Abstract. 3D City models are essential for urban planning, accurately visualizing, analyzing, and simulating urban environments. They find applications in various fields like AEC (Architecture and Construction), urban and transportation planning, development and conservation processes, energy systems monitoring, and many more. Extensive datasets for the 3D City Models need to be organized following international standards to make them reusable and sharable for different stakeholders. Designing a Geodatabase (GeoDB) for a 3D city model is crucial for data management as it is helpful in the streamlined visualization and analysis of the city's features and relations among its objects. Over the years, 3D city models have evolved into Urban Digital Twins, offering dynamic real-time simulations of cities and even better management and analysis of urban processes. This transition from 3D city models to UDTs enhances decision-making by providing detailed insights into the dynamics of urban systems, enabling better urban management and planning. This research concentrates on building a GeoDB to support the UDT. The paper discusses the data acquisition, processing, and integration methodologies.Additionally, it highlights the significance of utilizing advanced remote sensing technologies such as aerial LiDAR and aerial photogrammetry to enhance the digital twin’s quality and richness in detail. The semantics of the built environment datasets are clarified and strictly defined for the most important UDT features, such as buildings, roads, trees, and other features. This will ensure everyone can interpret the data similarly, leading to better analysis and decision-making.

Conceptual Model of Graph-based Individual Tree and Its Utilization in Digital Twin and Metaverse of Urban Forest

Abstract. 3D city models are an important cornerstone in the development of digital twin cities, allowing for various analyses and simulations. CityGML, as an open standard for 3D city models, emphasizes five main aspects: scale or level of detail (LoD), semantics, geometry, topology, and appearance. One of the important elements in CityGML 3D city models is representation of vegetation. Vegetation in CityGML, especially individual trees, is still limited in terms of detail and resolution, reducing its effectiveness for specific applications. This paper proposes a graph-based conceptual model for individual trees that conforms to the CityGML v2.0 specification. The model refers to the morphological structure of a tree consisting of roots, trunk, and crown (including branches, twigs, and leaves), and considers the five main aspects of CityGML. By enhancing semantic information and geometric details, the model aims to provide an information-rich and realistic representation of individual trees in a 3D city environment. The 3D tree model created based on this conceptual model may be applicable in the development of digital twin urban forests and virtual forest simulations that utilize immersive technologies such as the metaverse. This research opens up new opportunities in the development of solitary vegetation objects through CityGML ADE by including more detailed semantic and topological information.

Augmented Reality for Air Quality Monitoring: Case Study in the Marche Region (Italy)

Abstract. Augmented Reality (AR) allows the real world to be enhanced through the overlapping of digital information generated by an algorithm or software amplifying the user's perception. In this research, the potential of AR is exploited by applying it to the problem of air pollution visualization to raise awareness of the issue. It is well known that the principal sources of air pollution include industry, domestic heating, traffic, production processes and more others. According to European Environment Agency, air pollution is the largest environmental health risk in Europe in 2022 affecting respiratory and cardiovascular diseases and premature deaths. A suitable combination of GIS-based procedures for data analysis and georeferencing, AR systems for the visualization and exploitation of the results, can be a strategic driver. The research presented in this paper has been experimented in the Marche Region, in the central part of Italy, and in particular the city of Ancona. The pollutant data collected come from 17 Agenzia Regionale per la Protezione Ambientale delle Marche (ARPAM) meteorological ground-based stations located in Marche Region. The data processing have been executed using the software ArcGis Pro instead of a 3D City Model has been acquired from the online 3D ArcGIS platform. According to the Dlgs.155/2010 regulation, the AQI index (Air Quality Index) has been provided by the interpolation of the meteorological ground stations data. The visualization phase has been tackled exploiting in a WebGIS platform and an APP by AR. A 3D immersive visualization is made using five AQI level of air quality (excellent, good, fair, poor, bad) in order to increase the urban sensing.

Comparison Study of Three Building Regularization Algorithms

Abstract. Building outline generation and regularization is an ongoing topic in remote sensing applications. The success of the methods used for building outline detection impacts studies that depend on the accuracy of the methods applied, such as urban planning, geospatial analysis, and 3D city modeling. The results of the building outline detection methods can vary due to several factors, such as the area to which they are applied and/or the parameters used for the methods. Since there are well-established deep-learning based software and plugins for building outlining, this paper compares the results of such a method, namely an open-source AI implementation (Mapflow), with the standard non-deep-learning based tools introduced by (Mousa et al., 2019) and (Bulatov et al., 2014). We present a comparative analysis of these two methods for regularizing building outlines in terms of accuracy, efficiency, and robustness in dealing with different levels of buildings’ complexity and structures. While the results of (Mousa et al., 2019) and (Bulatov et al., 2014) are comparable and outperform the AI method, (Mousa et al., 2019) is the method least impacted by the different parameters, however, has a higher computing time.

Possibility of Substitution of LOD1 Data for LOD2 Data on Photovoltaic Potential Estimation at City Districts Level Using a 3D City Model

Abstract. We developed a system to estimate the photovoltaic (PV) potential of urban buildings using a 3D city model at level of detail 2 (LOD2), considering an arrangement of solar panels. Although the PV potential estimation of buildings at the level of city districts prefers LOD2 data, many urban city districts with buildings capable of installing solar panels on façades do not have LOD2 data owing to the high production cost of LOD2 data. Therefore, we investigated the possibility of utilising LOD1 data instead of LOD2 data in the PV potential estimation of buildings at the level of city districts. We conducted an experiment in the investigation using 3D city model data from 24 city districts, which are most of the large cities with LOD2 data in Japan. The experiment results suggest that LOD1 would not be a substitute for LOD2 data in the PV potential estimation of building roofs. The cause of the inadaptability is that most roofs in LOD2 buildings have more small polygons than LOD1 building roofs. Roofs of a LOD2 building with many small polygons have fewer solar panels than roofs of a LOD1 building with a large polygon. On the contrary, the experiment results indicate that LOD1 may be a substitute directly for LOD2 in the PV potential estimation of building façades that are expected to be used as a mounting platform for solar panels in urban buildings from now on. The average of the relative differences in the calculated PV potential of building façades between using LOD1 data and using LOD2 data is approximately 10% in the experiment.

Applications for Semantic 3D Streetspace Models and Their Requirements—A Review and Look at the Road Ahead

In addition to geometric accuracy, topological information, appearance and georeferenced data, semantic capabilities are key strengths of digital 3D city models. This provides the foundation for a growing number of use cases, far beyond visualization. While these use cases mostly focused on models of buildings or the terrain so far, the increasing availability of data on roads and other transportation infrastructure opened up a range of emerging use cases in the field of semantic 3D streetspace models. While there are already a number of implemented examples, there is also a potential for new use cases not yet established in the field of 3D city modeling, which benefit from detailed representations of roads and their environment. To ensure clarity in our discussions, we introduce an unambiguous distinction between the terms `application domain’, `use case’, `functionality’ and `software application’. Based on these definitions, use cases are categorized according to their primary application domain and discussed with respect to relevant literature and required functionalities. Furthermore, requirements of functionalities towards semantic 3D streetspace models are determined and evaluated in detail with regard to geometric, semantic, topological, temporal and visual aspects. This article aims to give an overview on use cases in the context of semantic 3D streetspace models and to present requirements of respective functionalities, in order to provide insight for researchers, municipalities, companies, data providers, mapping agencies and other stakeholders interested in creating and using a digital twin of the streetspace.

Трехмерное моделирование городов: исторические реконструкции и альтернативная реальность

The paper considers the technology of creating 3D models of cities, photogrammetric and other ways of their construction. The author shows projects created on the basis of this technology - 3D models of Yaroslavl, Moscow and St. Petersburg. The paper also describes the essence and results of the research performed on the basis of the constructed three-dimensional urban planning models. The paper presents historical recreation projects of cities for different time periods: Yaroslavl at the beginning of the XX century and Moscow at the XIX-beginning of the XX century. The author presents a list of monuments lost in reality, but recreated in a virtual three-dimensional environment and inscribed in the 3D model of the city. The paper presents a project involving the modelling of unrealised projects of avant-garde architects, as well as projects of the 1930s-1970s on the basis of a Moscow 3D model. The author concludes about the growing popularity of such digital models and the penetration of augmented and virtual reality technologies into our daily life.

Three-Dimensional Web-Based Client Presentation of Integrated BIM and GIS for Smart Cities

Smart cities use technological solutions to reduce the drawbacks of urban living. The importance of BIM and GIS integration has increased with the popularity of smart city and 3D city concepts in recent years. In addition to 3D city models, Building Information Modeling (BIM) is an essential element of smart cities. The 3D city model web client in this study displays three-dimensional (3D) city models created using photogrammetric techniques, BIM, and campus infrastructure projects. The comparison and integration of the aforementioned systems were evaluated. A web-based 3D client framework and implementation for combined BIM and 3D city models are the goals of the submitted work. The Web is a very challenging platform for 3D data presentation. The Cesium engine based on HTML5 and WebGL is an open-source creation and the virtualcityMAP application using the Cesium infrastructure was used in this study.

Focusing on individual buildings within urban contexts through generalisation levels: an interdisciplinary approach to the visualization of 3D-city models

Focusing on individual buildings within urban contexts through generalisation levels: an interdisciplinary approach to the visualization of 3D-city models

Identifying Legal, BIM Data and Visualization Requirements to Form Legal Spaces and Developing a Web-Based 3D Cadastre Prototype: A Case Study of Condominium Building

Over the past decade, numerous countries and researchers have been investigating the potential of 3D cadastre based on the Building Information Model (BIM). In Türkiye, the General Directorate of Land Registry and Cadastre (GDLRC) has been engaged in the “Production of 3D City Models and Creation of 3D Cadastral Bases Project” since 2018. One of the objectives is to develop 3D (physical) digital building models (and databases) through the digitization of floor plans of architectural drawings. In order to ensure the long-term viability of this project, a new regulation was issued in 2021. This regulation mandates the submission of 3D digital building models to the land registry in order to register condominiums. The future goals of the GDLRC include utilizing the 3D digital building models produced to create legal spaces in condominium buildings for the 3D cadastre. However, no research has yet been carried out for this goal. The objective of this research is to identify the legal and BIM data requirements for deriving legal spaces in condominium buildings, in light of the legislative analysis, and to develop a web-based 3D cadastre visualization prototype (showing both legal spaces and physical objects) based on the requirements obtained from the scientific literature. The result of this research demonstrates that well-structured and annotated BIM data can be used to develop a 3D cadastre prototype that meets the legal requirements in the case of Türkiye. Moreover, it is evident that, although the GDLRC has initiated the construction of a robust foundation for a 3D cadastre based on BIM, further enhancements and resolutions must be implemented from a legal and technical standpoint. It is postulated that the identified requirements and the proposed methodology in this research may assist decision-makers in Türkiye and globally in formulating their strategic plans for a 3D cadastre.

Multi-frequency smartphone positioning performance evaluation: insights into A-GNSS PPP-B2b services and beyond

In August 2023, Xiaomi unveiled the Redmi K60 Ultra, the first multi-frequency smartphone integrated with BeiDou-3 Navigation Satellite System Precise Point Positioning (PPP-B2b) services and employing PPP technology as the primary positioning method. The positioning enhancement service is provided by the Assisted Global Navigation Satellite System (A-GNSS) location platform developed by the China Academy of Information and Communications Technology. The signaling interaction between the server and the users strictly adheres to the Third Generation of Mobile Communications Technology Partnership Project Long-Term Evolution Positioning Protocol and the Open Mobile Alliance Secure User Plane Location framework. To comprehensively evaluate the Redmi K60 Ultra’s capabilities, this study designed six distinct experimental scenarios and conducted comprehensive research on multi-frequency and multi-GNSS observation noise, Time to First Fix (TTFF), as well as the performance of both GNSS-based and network-based positioning. Experimental results indicate that the GNSS chipset within the Redmi K60 Ultra has achieved a leading position in the consumer market concerning supported satellite constellations, frequencies, and observation accuracy, and is comparable to some low-cost GNSS receivers. A-GNSS positioning can reduce the TTFF from 30 to under 5 s, representing an improvement of over 85% in the cold start speed compared to a standalone GNSS mode. The positioning results show that the A-GNSS PPP-B2b service can achieve positioning performance with RMS errors of less than 1.5 m, 2.5 m, and 4 m in open-sky, realistic, and challenging urban environments. Compared to GNSS-based positioning, cellular network-based Observed Time Difference of Arrival (OTDOA) positioning achieves an accuracy ranging from tens to hundreds of meters in various experimental scenarios and currently functions primarily as coarse location determination. Additionally, this study explores the potential of the Three-Dimensional Mapping-Aided (3DMA) GNSS algorithm in detecting Non-Line-of-Sight signals and enhancing positioning performance. The results indicate that 3DMA PPP, as compared to conventional PPP, can significantly accelerate PPP convergence and improve positioning accuracy by over 30%. Consequently, 3D city models can be utilized as future assistance data for the A-GNSS location platform.

Extension of HBIM to 3D city modeling: Application for the port city of Massawa, Eritrea

Despite the significance of 3D city models, the associated costs and reliance on modern data acquisition tools hindered progress. This research aims to bridge these gaps by devising a method to create 3D city models with limited resources, sidestepping the need for cutting-edge tools. The method proposed relies on available resources to generate building footprint data and primarily generates elevation data using images. Based on Historic Building information model principles, a 3D city model of the port city of Massawa, Eritrea, comprising four classes of models was developed. In its current state, the model can be used for several applications such as visualization, conservation, urban assessments, and as a spatial data source to develop a city digital twin. Despite limitations in acquiring appropriate resources and the need for significant user interaction, the approach holds promise for initiating urban heritage conservation, particularly in inaccessible and resource-deficient sites in developing countries.

A framework for fully automated reconstruction of semantic building model at urban-scale using textured LoD2 data

The CityGML Level of Detail 3 (LoD3), a widely adopted standard for three-dimensional (3D) city modeling, has been accessible for an extended period. However, its comprehensive implementation remains limited due to challenges such as insufficient automation and inconsistent data quality. This research introduces an innovative and fully automated framework aimed at urban-scale semantic building model reconstruction. The proposed framework addresses three critical challenges: (1) proposing facade layout graph model to formalize the geometry and topological relationships of semantic entities on building facades, thereby promoting the deduction of structural completeness and the reconstruction of semantic facade models; (2) establishing a mapping relationship between texture images, semantic entities, and building shells guided by the facade layout graph to ensure consistent correlations among the geometry, semantics, and topology of building models; (3) developing an efficient representation methodology for semantic building models utilizing a parameter set derived from the facade layout graph. The proposed framework has been successfully validated by reconstructing 8,681 buildings from three different locations in Berlin. The results demonstrate an outstanding reconstruction accuracy of 91%, with a time efficiency of only 3.42 s per building. Visual analysis further confirms that the framework effectively fulfills the application prerequisites of 3D GIS. The code of the proposed framework is available in the repository: https://github.com/wangyuefeng2017/LoD3Framework-.

Large-Scale Solar Potential Analysis in a 3D CAD Framework as a Use Case of Urban Digital Twins

Solar radiation impacts diverse aspects of city life, such as harvesting energy with PV panels, passive heating of buildings in winter, cooling the loads of air-conditioning systems in summer, and the urban microclimate. Urban digital twins and 3D city models can support solar studies in the process of urban planning and provide valuable insights for data-driven decision support. This study examines the calculation of solar incident radiation at the city scale in Sofia using remote sensing data for the large shading context in a mountainous region and 3D building data. It aims to explore the methods of geometry optimisation, limitations, and performance issues of a 3D computer-aided design (CAD) tool dedicated to small-scale solar analysis and employed at the city scale. Two cases were considered at the city and district scales, respectively. The total face count of meshes for the simulations constituted approximately 2,000,000 faces. A total of 64,379 roofs for the whole city and 4796 buildings for one district were selected. All calculations were performed in one batch and visualised in a 3D web platform. The use of a 3D CAD environment establishes a seamless process of updating 3D models and simulations, while preprocessing in Geographic Information System (GIS) ensures working with large-scale datasets. The proposed method showed a moderate computation time for both cases and could be extended to include reflected radiation and dense photogrammetric meshes in the future.

Elaborating and performing optimization approaches for web-based 3D spatial analysis of 3D city models

ABSTRACT Three-dimensional (3D) geographic information systems (GIS) are vital for urban planning and architectural design, enabling detailed visualization and analysis of urban landscapes. However, the growing size of 3D city data and the transition to web environments cause performance challenges for real-time applications. This study addresses the need for optimizing 3D spatial analyses for the web using Quadtree data structures and multiprocessing tools. Optimization scenarios based on data size and hardware configurations are evaluated, and the best hosting plans for GIS applications on cloud services are also considered.

Integrating human perception in 3D city models and urban digital twins

Integrating human perception in 3D city models and urban digital twins

High resolution solar potential computation in large scale urban areas by means of semantic 3D city models

High resolution solar potential computation in large scale urban areas by means of semantic 3D city models

Enriching lower LoD 3D city models with semantic data computed by the voxelisation of BIM sources

Enriching lower LoD 3D city models with semantic data computed by the voxelisation of BIM sources