Our Research
Spatial analysis and modelling have been long-standing research strengths at Â鶹´«Ã½. This began with the Social Science Research Council-funded Regional Research Laboratory in the 1980s.
Our International reputation
Spatial analytics and modelling are key contributors to the high international ranking and reputation of Â鶹´«Ã½. We have an established international reputation, especially in:
- theory-led spatial analysis and policy applications at the city and city-regional scales
- spatial risk impact assessment and infrastructure systems
- scalable and cloud computing and visualisation
Reputation and ranking
| Research area | Research power | REF ranking | QS ranking (2015) |
|---|---|---|---|
| Architecture and Planning | 4th | 10th out of 45 | n/a |
| Geography | 16th | 10th out of 57 | 31 |
| Engineering | 3rd | 6th out of 14 | 45 |
| Computing Science | 9th | 9th out of 89 | n/a |
| Mathematics and Statistics | 30th | 11th out of 53 | n/a |
Expanding expertise
Spatial Analytics and Modelling at Â鶹´«Ã½ will integrate, and build capacity and expertise in this rapidly expanding area.
Building up expertise in spatial analytics and modelling is about positioning the University to
- take advantage of the fruitful research context
- address the urban science and wider future cities and sustainable agendas
- add significant value to University investment in these areas
The HASS and SAgE faculty collaboration adds value by connecting and forging transdisciplinary approaches. The investment comprises four chair-level posts situated in and connected between:
- CURDS and Geography
- Architecture and Planning
- Engineering
- Mathematics and Statistics
Spatial Analytics and Modelling at Â鶹´«Ã½ has a remit to engage with Computing Science, the Digital Institute and National Institute for Smart Data Innovation (NISDI), as well as the:
- Institute for Sustainability
- School of Marine Science and Technology
- University's four ESPRC/NERC-funded Centres for Doctoral Training
- ESRC Doctoral Training Centre with Durham University
Research themes
Spatial Analytics and Modelling at Â鶹´«Ã½ will focus on further advancing and developing existing and novel research themes, challenges and applications. We will achieve this through research income generation, published outputs, engagement and impact.
Research areas:
- New big data tools and techniques for the capture, analysis, modelling and management of complex social, economic, engineered and natural systems across a range of spatial scales from micro to global.
- Next generation spatio-temporal simulation and modelling approaches for trans-disciplinary integrated assessment.
- Improved spatio-temporal and real-time decision support tools for the engineering, natural and social sciences.
- Transformative spatio-temporal visual analytics for improved policy and governance choices in an uncertain world.
- Innovative visualisation methods for exploring spatial data and engaging in a range of public, private and civic stakeholders in decision-making.