Speaker
Description
The integration of emerging technologies into urban planning is essential for addressing complex societal challenges in the UK, including sustainable solutions for the exacerbated rise in housing demand (Wilson & Barton, 2023). The NERC-funded £8M Digital Solutions Hub (DSH), a cutting-edge GIS-powered platform, has designed a digital tool to help policymakers arrive at evidence-based decisions on where, how and when to build. This paper explores the transformative potential of DSH’s “where-to-build” tool, leveraging geospatial analytics, real-time data, and advanced decision-support frameworks to optimize housing expansion in the UK.
The tool speaks to the ambitious UK housing strategy of building 1.5 million homes over the next five years (Haughton et al., 2024). The tool focuses on the need for policymakers to ensure a balance between multiple factors while taking into account context-specific spatial considerations: 1. Land suitability and environmental considerations – integrating environmental datasets such as soil quality, water supply, flood risk and biodiversity hotspots, with socioeconomic datasets such as land use patterns and demographics is essential. 2. Infrastructure and connectivity – inclusion of real-time data and GIS-based models enables adaptive planning based on the connectivity between housing developments and their surrounding networks such as transport networks, public utilities and other essential services, incorporated with the socioeconomic and environmental data within the tool. 3. Supporting decarbonisation and climate adaptation – utilising GIS technology to enable planners to assess climate risks of new housing sites and explore opportunities for incorporating renewable energy sources ensures the outcome decisions adhere to UK environmental policies. This is achieved through integrating models to analyse how different developments interact with energy demand, emissions and natural carbon sinks.
“Where-to-build” is one of a suite of digital tools developed under the DSH umbrella as part of a 4-year research programme. The tool has been in the making for two years with the involvement of multiple expertise in housing, planning, environmental management, GIS technologies and stakeholder engagement. The team followed a comprehensive approach starting with stakeholder workshops to elicit what policymakers would like to see in the tool, followed by intensive development work to gather, curate and analyse the abovementioned data and models to formulate the building blocks of a transformative tool. The final stage is usability testing, taking place in 2025, with different policy, academic and third sector users invited to test and feedback on the tool design before its official launch.
The paper underscores the importance of adopting emerging technologies in urban planning, showcased through the practical application of our DSH UK-wide housing tool. The DSH demonstrates how GIS-powered platforms can bridge the gap between data and decision-making, fostering innovative and sustainable solutions. This approach not only addresses immediate housing needs but also aligns with long-term goals of resilience and climate adaptation in UK policy (Foley et al., 2005; UK Climate Change Committee, 2021).
References
Foley, J. A. et al. (2005). Global Consequences of Land Use. Science, 309, 570–574. https://doi.org/10.1126/science.1111772
Haughton, G., Nanda, A. & Kingston, R. (2024, July). The new Labour government plans to build 1.5 million homes – here’s what’s needed to make it happen. The Conversation. https://theconversation.com/the-new-labour-government-plans-to-build-1-5-million-homes-heres-whats-needed-to-make-it-happen-234599
UK Climate Change Committee. (2021). Progress in Reducing Emissions: 2021 Report to Parliament (Issue June). https://www.theccc.org.uk/publication/2021-progress-report-to-parliament/
Wilson, W., & Barton, C. (2023). Tackling the under-supply of housing in England. House of Commons Library, Briefing Paper 07671, 80.
| Keywords | GIS technology; sustainable housing; geospatial analytics; decision-support tools |
|---|---|
| Best Congress Paper Award | Yes |
