In spatial science and urban applications, “space" is presented by multiple disciplines as a notion referencing our living environment. Space is used as a general term to help understand particular characteristics of the environment. However, the definition and perception of space varies and these variations have to be harmonised. For example, space may have diverse definitions and classification, the same environment may be abstracted/modelled by contradicting notions of space, which can lead to inconsistencies and misunderstandings. In this paper, we seek to investigate and document the state-of-the-art in the research of “space” regarding its definition, classification, modelling and utilization (2D/3D) in spatial sciences and urban applications. We focus on positioning, navigation, building micro-climate and thermal comfort, landscape, urban planning and design, urban heat island, interior design and planning, transportation and intelligent space. We review 147 research papers, technical reports and on-line resources. We compare the presented space concepts with respect to five criteria—classification, boundary, modelling components, use of standards and granularity. The review inventory is intended for both scientists and professionals in the spatial industry, such as companies, national mapping agencies and governments, and aim to provide a reference to better understand and employ the “space” while working across disciplines.

In recent years, the concept of Digital Twin (DT) for cities is increasingly at the core of most smart city initiatives, as it has been identified as a critical tool for tackling the challenges of this century. A robust city modelling framework is essential if local, state and national governments are to move towards sustainable built environments and work together across complex multi-sectoral problems to drive impacts that improve urban liveability and climate adaptability. Furthermore, the level of collaboration and interoperability required to address these cannot be achieved without proper standardisation of DT components. The aim of this project is to develop a demonstration DT that integrates existing data using a standardised 3D format based on CityGML and that embeds analytics, such as sun exposure and tree coverage, to assess liveability within a 3D city modelling framework. Common urban features such as buildings, roads, railways, vegetation and water bodies are also processed and incorporated. Additionally, IoT sensors are integrated into the model and all processes are performed using open-source tools to improve accessibility and repeatability. Details of the workflow, including the storage of the city features in a 3D City Database (3DCityDB), the 3D upgrading of urban features commonly available as 2D data as well as a few use cases are illustrated and discussed in this paper.

This paper presents the research and development of a volumetric 3D visibility analysis application to assess public space in regards to safety and security. While most of the academic literature on space visibility concentrates on developing viewsheds from a specific viewpoint, this work integrates dynamic scenarios and real-time calculation of space visibility. Voxel-based spatial representation is utilised as a base for the 3D visibility analysis. Different space configurations are tested illustrating the robustness and usefulness of the developed application. In order to measure and evaluate different safety zones, an innovative approach is tested according to which the number of times each voxel is observed is recorded and further classified into different zones. In this way, an accurate calculation of the observed space can be performed understanding which part of an area of interest is less or more observed. The research has shown great potential for first responders, researchers, architects and safety experts. The developed application can be used as a simulation tool to assess the safety of different urban environments and identify potentially vulnerable locations.

An indoor logical network qualitatively represents abstract relationships between indoor spaces, and it can be used for path computation. In this paper, we concentrate on the logical network that does not have notions for metrics. Instead, it relies on the semantics and properties of indoor spaces. A navigation path can be computed by deriving parameters from these semantics and minimizing them in routing algorithms. Although previous studies have adopted semantic approaches to build logical networks, routing methods are seldom elaborated. The main issue with such networks is to derive criteria for path computation using the semantics of spaces. Here, we present a routing mechanism that is based on a dedicated space classification and a set of routing criteria. The space classification reflects characteristics of spaces that are important for navigation, such as horizontal and vertical directions, doors and windows, etc. Six routing criteria are introduced, and they involve: (1) the spaces with the preferred semantics; and/or (2) their centrality in the logical network. Each criterion is encoded as the weights to the nodes or edges of the logical network by considering the semantics of spaces. Logical paths are derived by a traditional shortest-path algorithm that minimizes these weights. Depending on the building’s interior configuration, one criterion may result in several logical paths. Therefore, we introduce a priority ordering of criteria to support path selection and decrease the possible number of logical paths. We provide a proof-of-concept implementation for several buildings to demonstrate the usability of such a routing. The main benefit of this routing method is that it does not need geometric information to compute a path. The logical network can be created using verbal descriptions only, and this routing method can be applied to indoor spaces derived from any building subdivision.

One of the significant challenges facing the development of web portals is optimising the usability of such e-infrastructures for diverse, yet specialised, uses. This paper presents a usability framework for supporting the iterative testing and development of the Australian Urban Research Infrastructure Network (AURIN) portal. The portal serves as a securitised environment for data sharing, and as a repository of open-source analytical routines to support urban decision-making. Harmonisation, security, accessibility and discoverability are critical concerns at the data level as many different kinds of federated data are being referenced by the portal. Furthermore, urban researchers are accessing this portal across Australia as an advanced spatial decision support system. A further design consideration for the portal is that it needs to be able to be usable by non-experts to discover and access a broad spectrum of digital data and analytical tools relevant to human settlements. Managing the complexity across many areas and supporting a spectrum of naïve to expert users are significant challenges. In this research we present an overview of a usability framework, developed for the AURIN project, which elicits feedback from naïve users through to domain experts. This feedback is captured through hands-on workshops with participants and one-on-one user testing sessions. In this paper we report the findings from initial workshops with end-users and one-on-one testing sessions. We analyse this feedback to understand the current strengths and weaknesses of the system. The end-user feedback provides a dual purpose. Firstly, it is fed back to the technical development team as part of a cycle of continuous improvement. Secondly, the workshops also provide a vehicle for engaging end-users and raising awareness of the AURIN data search, interrogation and visualisation capabilities. We conclude the paper by discussing the next steps in developing and implementing the usability framework in relation to the AURIN portal.