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In the last decades, 3D city models appear to have been predominantly used for visualisation; however, today they are being increasingly employed in a number of domains and for a large range of tasks beyond visualisation. In this paper, we seek to understand and document the state of the art regarding the utilisation of 3D city models across multiple domains based on a comprehensive literature study including hundreds of research papers, technical reports and online resources. A challenge in a study such as ours is that the ways in which 3D city models are used cannot be readily listed due to fuzziness, terminological ambiguity, unclear added-value of 3D geoinformation in some instances, and absence of technical information. To address this challenge, we delineate a hierarchical terminology (spatial operations, use cases, applications), and develop a theoretical reasoning to segment and categorise the diverse uses of 3D city models. Following this framework, we provide a list of identified use cases of 3D city models (with a description of each), and their applications. Our study demonstrates that 3D city models are employed in at least 29 use cases that are a part of more than 100 applications. The classified inventory could be useful for scientists as well as stakeholders in the geospatial industry, such as companies and national mapping agencies, as it may serve as a reference document to better position their operations, design product portfolios, and to better understand the market.

This paper introduces Property Valuation Application Domain Extension (ADE) within CityGML 3.0, aiming to integrate relevant indoor and outdoor 3D variables (cost estimation, view quality, etc.) for accurate property valuation. Current models lack the necessary features for this specific application. Leveraging IFC data for indoor elements, this ADE extends CityGML, addressing the existing gap. This paper identifies and categorizes data requirements, leading to the conceptualization and development of the model. By enriching CityGML 3.0 with IFC data, the approach introduces new features like the \"Property Unit\" to ensure adaptability across diverse valuation scenarios. Despite encountering data integrability challenges, we here commit to refining the model and overcoming these obstacles. A preliminary implementation using CityJSON demonstrates successful integration and paves the way for future implementation. These include developing an API platform and establishing an official repository to facilitate practical usability and scalability. This research significantly contributes to advancing property valuation processes by providing accurate valuations for stakeholders and promoting the use of 3D urban data in domain-specific extensions.

Singapore, branded as a “City in a Garden”, has a long standing commitment to green the nation, one which has resulted in trees becoming an integral component of the urban environment. Similarly for its digital twin, Virtual Singapore, we undertake the research to automate the population of this virtual city with semantically and biologically representative trees in a CityGML (City Geography Markup Language) format. This paper presents our framework of modeling trees for Virtual Singapore, showcasing an array of methodologies in data acquisition of light detection and ranging (LiDAR) and satellite images, tree extraction and quantification, and 3D tree modeling at LODs (level of details) 1, 2 and 3. The paper will also highlight challenges and chosen methodologies along with the preliminary results of this framework.

This paper aims to describe the outcomes of the Main10ance project, which focused on developing an integrated HBIM-GIS platform to support the maintenance and conservation plans for the historic built heritage. The pilot case is the UNESCO complex of the Sacri Monti, located in northern Italy and Switzerland, which consists of groups of chapels and architectural artifacts holding significant historical and cultural value. Given their importance, specific maintenance plans involving multiple stakeholders and specialists are required. This study focuses on creating a unified system that semantically and spatially describes the architectural elements of the case study and the surrounding context and indoor assets. After a 3D integrated metric survey and the related data processing, parametric 3D models were created in a BIM environment, and a spatial database was developed to incorporate both geometric and alphanumeric entities. The database enables interoperability among different actors and domains, gathering heritage-related information crucial for restoration and conservation purposes. Additionally, the custom 4MAIN10ANCE web platform was developed with different levels of details (LODs), enabling the retrieval of both 2D and 3D data and establishing connections between the BIM models of the chapels and associated information.

According to CityGML, 3D models at different Levels of Details (LoDs) are defined to meet the geometric requirements of various applications. Following this principle, this paper introduces a concept of LoDs for the 3D modeling of Buddhist statues. The procedure consists of four steps: (1) inventory of applications, (2) analysis of geometric requirements in applications, (3) determination of the number of LoDs, and (4) design of geometric representations of each LoD. Based on 60 application scenarios, we proposed four LoDs for Buddhist statue modeling. LoD1 is defined as 2D symbols for geospatial analysis, LoD2 uses convex hull geometry for GIS applications, LoD3 is represented by coarse solid boundary representation of primary components for applications such as conservation and transportation, and LoD4 models detailed geometries for every small component to support various types of archeology calculations. The key feature of the proposed LoD concept is the integration of semantic information, which serves as fundamental data for interoperability in computer-aided applications. Based on the proposed LoD in this paper, a CityGML Application Domain Extension (ADE) can be developed for the 3D digital modeling of Buddhist statues or even figure sculptures more broadly. The procedure developed in this paper could be generally used to design LoDs for other types of features in context with their application needs. Although this study focuses on Buddhist statues, the proposed LoD framework is adaptable to other sculptural traditions that require semantic-aware modeling, thereby enabling broad applicability across different cultural heritage domains.

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.

The growing interest in building data management, especially the building information model (BIM), has significantly influenced urban management, materials supply chain analysis, documentation, and storage. However, the integration of BIM into 3D GIS tools is becoming more common, showing progress beyond the traditional problem. To address this, this study proposes data transformation methods involving mapping between three domains: industry foundation classes (IFC), city geometry markup language (CityGML), and web ontology framework (OWL)/resource description framework (RDF). Initially, IFC data are converted to CityGML format using the feature manipulation engine (FME) at CityGML standard’s levels of detail 4 (LOD4) to enhance BIM data interoperability. Subsequently, CityGML is converted to the OWL/RDF diagram format to validate the proposed BIM conversion process. To ensure integration between BIM and GIS, geometric data and information are visualized through Cesium Ion web services and Unreal Engine. Additionally, an RDF graph is applied to analyze the association between the semantic mapping of the CityGML standard, with Neo4j (a graph database management system) utilized for visualization. The study’s results demonstrate that the proposed data transformation methods significantly improve the interoperability and visualization of 3D city models, facilitating better urban management and planning.

Applications of 3D City Models range from assessing the potential output of solar panels across a city to determining the best location for 5G mobile phone masts. While in the past these models were not readily available, the rapid increase of available data from sources such as Open Data (e.g. OpenStreetMap), National Mapping and Cadastral Agencies and increasingly Building Information Models facilitates the implementation of increasingly detailed 3D Models. However, these sources also generate integration challenges relating to heterogeneity, storage and efficient management and visualization. CityGML and IFC (Industry Foundation Classes) are two standards that serve different application domains (GIS and BIM) and are commonly used to store and share 3D information. The ability to convert data from IFC to CityGML in a consistent manner could generate 3D City Models able to represent an entire city, but that also include detailed geometric and semantic information regarding its elements. However, CityGML and IFC present major differences in their schemas, rendering interoperability a challenging task, particularly when details of a building’s internal structure are considered (Level of Detail 4 in CityGML). The aim of this paper is to investigate interoperability options between the aforementioned standards, by converting IFC models to CityGML LoD 4 Models. The CityGML Models are then semantically enriched and the proposed methodology is assessed in terms of model’s geometric validity and capability to preserve semantics.

When producing an engaging augmented reality (AR) user experience, it is crucial to create AR content that mimics real-life objects’ behavior to the greatest extent possible. A critical aspect to achieve this is ensuring that the digital objects conform to line-of-sight rules and are either partially or completely occluded, just like real-world objects would be. The study explores the concept of utilizing a pre-existing 3D representation of the physical environment as an occlusion mask that governs the rendering of each pixel. Specifically, the research aligns a Level of Detail (LOD) 1 building model and a 3D mesh model with their real-world counterparts and evaluates the effectiveness of occlusion between the two models in an outdoor setting. Despite the mesh model containing more detailed information, the overall results do not show improvement. In an indoor scenario, the researchers leverage the scanning capability of HoloLens 2.0 to create a pre-scanned representation, which helps overcome the limited range and delay of the mesh reconstruction.

Floods are one of the most frequent types of destructive natural disaster that causes serious safety risks and economic losses. Flood simulation has been an effective way to model the behavior and dynamics of flood and support the analysis like flood disaster assessment. Currently, most 3D flood simulations often take heterogenous data (e.g. flood measurements, terrain data) as input for calculation, but lack a unified representation of these data, and the environment objects are normally modeled in a simplified manner with only geometric information while neglecting their semantics. To address this gap, this study developed a CityGML Flood Application Domain Extension (Flood ADE) for representing and storing flood information along with semantic information of 3D urban objects. We presented the methodology for developing the CityGML Flood ADE and described its thematic modules. The effectiveness of the developed Flood ADE is demonstrated by using 3D building data and flood data in the Lundamo area of the Sokna River, Trondheim, Norway. This work will not only support flood prevention decisions, analysis, and post-disaster assessments, but also promote cross-departmental collaborations.