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Although digital twins have been established in manufacturing for a long time, they are only more recently making their way into the urban environment and present a relatively new concept for the construction industry. The concept of a digital twin—a model of the physical environment that has a real-time two-way link between the physical and the digital, with the virtual model changing over time to reflect changes in the real world—lends itself well to the continually changing environment of a construction project. Predictive capabilities built into a twin also have great potential for construction planning—including in supply chain management and waste disposal as well as in the construction process itself. Underpinning this opportunity is location data, which model where something is happening and when and can be used to solve a wide range of problems. In particular, location (the power of where) can integrate diverse data sources and types into a single system, overcoming interoperability challenges that are known to be a barrier to twin implementation. This paper demonstrates the power of location-enabled digital twins in the context of a highway construction project, documenting and addressing data engineering tasks and functionality development to explore the potential of digital twins in the context of two case studies—health and safety and construction monitoring. We develop two demonstrators using data from an existing construction project (building on data and requirements from industry partner Skanska) to build twins that make use of the powers of 4D data presentation offered by the Unreal Gaming Engine and CesiumJS mapping, while software development expertise is sometimes available to construction firms, we specifically explore to what extent the no-code approach available within Unreal can be deployed in this context. Our findings provide evidence to construction companies as to the benefits of digital twins, as well as an understanding of the data engineering and technical skills required to achieve these benefits. The overall results demonstrate the potential for digital twins to unlock and democratise construction data, taking them beyond the niche use of experts and into the boardroom.

Delivering value from digital concepts such as Digital Twins is necessary to address systemic national and global issues, such as achieving Net Zero. However, there is still a lack of consensus over what a Digital Twin (DT) is and efforts to clarify this do not consider the Geospatial perspective. With the aspiration for national- and international-scale DTs, it is important that the Geospatial community understands its role in supporting the realisation of the value of these DTs. Here, a systematic literature review is used to gather DT case studies that use, or are inferred to use, elements of the Geospatial discipline. A total of 77 DT case studies about smart cities, manufacturing, energy, construction and agriculture are reviewed in full, and 24 Geospatial DT dimensions are defined and then compared with existing DT dimensions. The results indicate a considerable use of Geospatial Science in DTs that is not explicitly stated, meaning that there are possibly missed opportunities for collaboration between the Geospatial and DT communities. We conclude that the role of Geospatial Science in DTs is larger than stated and needs to be understood further.

In both the Geospatial (Geo) and Building Information Modelling (BIM) domains, it is widely acknowledged that the integration of geo-data and BIM-data is beneficial and a crucial step towards solving the multi-disciplinary challenges of our built environment. The result of this integration—broadly termed GeoBIM—has the potential to be particularly beneficial in the context of the construction of large infrastructure projects, which could make use of data relating to the larger spatial extents typically handled in geographical information systems (GIS) as well as the detailed models generated by BIM. To date, GeoBIM integration has mainly been explored for buildings, in a 3D context and for small projects. This paper demonstrates the results of the next level of integration, exploring the addition of the fourth dimension by linking project schedule information to create 4D GeoBIM, examining interoperability challenges and benefits in the context of a number of use cases relating to the enabling works for a major commercial infrastructure project. The integrating power of location and time—knowing where and when data relate to—allows us to explore data interoperability challenges relating to linking real world construction data, created using commercial software, with other data sources; we are then able to demonstrate the benefits of 4D GeoBIM in the context of three decision making scenarios: examining the potential for prioritisation of noise mitigation interventions by identifying apartments closest to the noisiest construction process; development of a 4D location-enabled risk register allowing, for example, work to continue underground if a risk is specific to the top of a building; ensuring construction safety by using 3D buffering to ensure that the required distances between moving construction equipment and surrounding infrastructure are not breached. Additionally, once integrated, we are able to ‘democratize’ the data—make it accessible beyond the BIM and GIS expert group—by embedding it into a 3D/4D open source Web GIS tool.

The integration of 3D city models with Building Information Models (BIM), coined as GeoBIM, facilitates improved data support to several applications, e.g., 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e., harmonization of features, interoperability, format conversions, integration of procedures. The GeoBIM benchmark 2019, funded by ISPRS and EuroSDR, evaluated the state of implementation of tools addressing some of those issues. In particular, in the part of the benchmark described in this paper, the application of georeferencing to Industry Foundation Classes (IFC) models and making consistent conversions between 3D city models and BIM are investigated, considering the OGC CityGML and buildingSMART IFC as reference standards. In the benchmark, sample datasets in the two reference standards were provided. External volunteers were asked to describe and test georeferencing procedures for IFC models and conversion tools between CityGML and IFC. From the analysis of the delivered answers and processed datasets, it was possible to notice that while there are tools and procedures available to support georeferencing and data conversion, comprehensive definition of the requirements, clear rules to perform such two tasks, as well as solid technological solutions implementing them, are still lacking in functionalities. Those specific issues can be a sensible starting point for planning the next GeoBIM integration agendas.

Interdisciplinary research with geographic information systems (GIS) can be rewarding as researchers from different disciplines have the opportunity to create something novel. GIS, though, is known to be difficult to use and learn. It is imperative for its successful use in projects that those who need to use GIS are able to learn it quickly and easily. To better support interdisciplinary research with GIS, it is necessary to understand what researchers with interdisciplinary experience wanted to use it for and how they learned it. The aim would be to advise geography educators on creating learning resources that could compliment or supplement existing learning approaches used by interdisciplinary researchers to improve the learning experience and uptake of GIS. This article explores the results from an online survey and interviews conducted between July 2014 and August 2015 with participants from the UK, the US and Europe on how interdisciplinary researchers learned GIS and which resources and platforms were utilised. Guidelines and a framework are presented, modifying the Technological Pedagogical and Content Knowledge framework, incorporating informal and context‐based learning and GIS concepts from the Geographic Information Science and Technology Body of Knowledge. Findings show that interdisciplinary researchers want to use GIS to capture, analyse and visualise information; they largely use informal learning approaches (e.g. internet searches, watching a video, ask a more experienced person); and they predominantly use ArcGIS, QGIS and web GIS platforms. Future work suggests resources use contextually relevant learning activities and bear in mind nuances of disciplinary language. Geography is quite complimentary to interdisciplinary research as is one of its most powerful tools ‐ geographic information systems (GIS); however, such systems are known to be difficult to use. To better support interdisciplinary research initiatives that use GIS, it is first necessary to understand how those involved in previous similar projects have gone about learning GIS. Based on those findings, the article outlines a framework and guidelines, reinforced by educational theory and GIS curriculum, on how to support interdisciplinary researchers when they are learning GIS.e00046

Digital twins (DTs) are digital representations of physical entities where data connections synchronise the physical and digital states at a specified frequency. While DTs originated in manufacturing and aerospace, they are increasingly applied at geographic scales addressing urban issues. As a result, DTs must utilise geospatial information (GI) to represent the built environment, though this is often an implicit aspect. Public sector geospatial information (PSGI), typically produced by National Mapping and Cadastral Agencies (NMCA) is a particular type of GI that serves as an authoritative, foundational component to geospatial applications. However, the value of this PSGI as foundation component of DTs is not well understood. Existing GI valuation methodologies do not account for the unique characteristics of foundational PSGI, or its role within DTs , leaving NMCAs unable to justify investment, and adapt their contributions, to emerging DTs. To address this gap, this study applies Jabareen’s (2009) conceptual framework analysis methodology to define what value means in the context of PSGI in DTs. The analysis identifies seven value enablers and five value dimensions that characterise PSGI value in DTs and provide the basis for future quantitative valuation methodologies. These concepts are integrated through an urban infrastructure DT example and synthesised through boundary case analysis. The resulting conceptual understanding enables NMCAs to systematically articulate and evidence their contributions to DTs.

As digital transformation accelerates in the construction industry, combining data from Building Information Modelling (BIM) and 3D Geographic Information Systems (3DGIS) has become critical for enhanced decision-making across sectors including construction planning, supply chain management, health and safety and sustainable waste disposal. In combination, BIM and GIS underpin a location framework for Digital Twins across these applications. While traditionally relational databases have been used to integrate the data into one system, they face increasing limitations in handling the massive, complex BIM and 3DGIS data. This research investigates the potential of NoSQL databases as an alternative solution. Focusing on MongoDB, the study conducts a systematic performance comparison with the mature relational database, PostgreSQL. BIM and 3DGIS datasets from a live infrastructure construction project are utilised in three experiments assessing direct query, API-based retrieval, and 3D visualisation. The results provide valuable insights into MongoDB’s strengths in managing large spatial data via flexible schemas. However, limitations surface as data complexity and volume increases. Overall, this study concludes that NoSQL databases do offer some advantages for optimising BIM-3DGIS integration for seamless, combined, use, but more work is needed to fully harness their capabilities.

Geographic data are used by United Kingdom (UK) defence for purposes including peacekeeping, humanitarian aid and disaster relief, and fighting wars. The geographic extent of defence data covers the world, with greater focus directed towards areas considered to be of current interest. Traditionally, these data have been officially sourced, e.g. via National Mapping Agencies, but there is now increasing interest in the potential of crowdsourced geographic data to supplement authoritative data where they are not available, outdated or incomplete. Volunteered geographic information (VGI) and social media have the potential to provide this needed missing information. This paper presents initial work carried out in identifying the potential of crowdsourced geographic information in defence. We first provide a short description of the role of UK defence and review the existing literature on crowdsourced geographic information in defence, as well as generic VGI quality assessment methods. We then explore the potential of crowdsourced data in real-world applications: the conflation of VGI and social media with official data for effective decision-making in war zones, and the potential for crowdsourcing to increase effective collaboration between machines and humans in disaster situations. Based on our review, we outline specific research challenges for deploying crowdsourced geographic information in defence, focussing on data quality and fitness-for-purpose assessment. Defence-specific constraints include the need for rapid quality assessment processes and the need to communicate high-quality information effectively in situations where rapid decision-making is required. Ethical issues are also of fundamental importance.

In an age of burgeoning open data sources, ranging from authoritative platforms to crowd-sourced contributions, the need for data integration is paramount - only with integrated, combined, data can today’s complex problems be addressed. However, assessing the quality of data and its potential for integration/interoperability is complex. FAIR (findable, accessible, interoperable and re-useable) approaches go some way to help, but most repositories still only offer text-based search results and require the user to download the data and assess its quality and fitness-for-purpose manually. This paper examines whether exploiting geospatial approaches - specifically, understanding whether a dataset can be mapped and hence integrated with other datasets - could address these issues, in particular for non-expert users. We explore challenges related to open data for education and environmental sustainability and introduce a novel, visual map-ability rating to assist data users in rapidly understanding the data quality and interoperability potential of data they wish to use. This rating system has been developed by researchers from outside the location science domain, to better reflect what is important to the wider community, and derives from a review of 104 open datasets. As well as providing useful insight to data users, the ratings can be used to guide data publishers as to how to improve their data offering.

A varied range of applications make use of 3D models nowadays, for instance in urban planning, energy demand studies, solar irradiation, or noise estimation. Acquisition, maintenance, and production of 3D spatial data is costly and laborious, especially at a national level, a great challenge for National Mapping and Cadastral Agencies (NMCAs) – such as Ordnance Survey (OS) for Great Britain. Generalisation is designed to address this challenge, where new datasets are created from a single source by the selection of the desired information and reduction of the amount of detail and data volume. Extensive literature exists in the context of 2D generalisation and automated algorithms exist to remove unwanted detail, however, adding a third dimension complicates the process significantly. Here, a methodology to address this issue is proposed, where the façades of a 3D building are decomposed, rotated, and translated from 3D environment to 2D. Existing automated 2D generalisation operators are applied to building elements and once generalised, they are rotated back to 3D. The outer shell of the resulting generalised 3D building is reconstructed with the independently generalised façade. The results demonstrate a potential flexible, component-based method for 3D generalisation, that could benefit NMCAs.