In practice, most planners do not make significant use of planning support systems. Although extensive research has been conducted, the focus tends to be on supporting individual tasks, and the outcomes are often the development of new stand-alone tools that are difficult to integrate into existing workflows. The knowledge contribution in this article focuses on developing a novel spatial decision support framework focusing on the workflows and tool-chains that span across different teams with varying skill sets and objectives, within an organisation. In the proposed framework, the core decision-making process uses a set of decision parameters that are combined using a weighted decision tree. The framework is evaluated by developing and testing a workflow and GIS tool-chain for a real-world case study of land suitability and mixed-use potentiality analysis.
Abstract. Efficient usage and management of abundant data are crucial for organisations, especially in the light of a lack of in-depth IT knowledge. Digital twins (DTs) are particularly expected to assist organisational processes, as behaviours of physical components are realistically represented by them using data for individual use cases. Nevertheless, DTs are extremely reliant on their use cases, leading to an extensive DT catalogue. However, a conclusive list of use cases for this accumulation of feasible DT application areas does not exist. To address this issue, this paper documents the use cases of Urban Digital Twin (UDT) platforms and applications with a state-of-the-art review. The study focuses on district-scale UDT applications that model, manage and analyse—buildings, transportation, energy, water, utility, and infrastructures that form smart cities. In order to catalogue diverse use cases found in several sectors, theoretical reasoning is developed. Our study provides a classified inventory that can be helpful for stakeholders in companies, government agencies and academia—such as researchers, architects, facilities managers, developers, and city planners.
Smart city initiatives have been a driving force for citylevel dataset collection and the development of data-driven applications that benefit effective city management. There is a need to demonstrate P. ALVA ET AL. development of data-driven applications that can help in effective city management. Smart cities have humans, technology and institutions as their three elements, with the environment, energy, transportation, safety, healthcare and education as fundamental disciplines. City sustainability, infrastructure, quality of life and service to the inhabitants are enhanced by smart city initiatives. A city-scale digital twin is one of the smart city initiatives that can integrate all disciplines mentioned above and improve systems' operability on a digital platform. Urban Digital Twin (UDT) is a 3D geospatial data model of a city consisting of physical assets, multimodal sensor data and bi-directional automated dataflow. Furthermore, planning and decision support is provided by UDTs to cities in terms of their administration, infrastructure, economic development, or citizen engagement (see Figure 1).
District-scale energy demand models can be powerful tools for understanding interactions in complex urban areas and optimising energy systems in new developments. The process of coupling characteristics of urban environments with simulation software to achieve accurate results is nascent. We developed a digital twin through a web map application for a 170ha district-scale university campus as a pilot. The impact on the built environment is simulated with pandemic (COVID-19) and climate change scenarios. The former can be observed through varying occupancy rates and average cooling loads in the buildings during the lockdown period. The digital twin dashboard was built with visualisations of the 3D campus, real-time data from sensors, energy demand simulation results from the City Energy Analyst (CEA) tool, and occupancy rates from WiFi data. The ongoing work focuses on formulating a resilience assessment metric to measure the robustness of buildings to these disruptions. This districtscale digital twin demonstration can help in facilities management and planning applications. The results show that the digital twin approach can support decarbonising initiatives for cities.
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