This part of the project will quantify, model and map vulnerabilities to poverty in energy and transport systems.
Visualising and mapping vulnerabilities
This part of the project will quantify, model and map vulnerabilities to poverty in energy and transport systems using a combination of primary and secondary data such as socio-demographics, housing, transport and energy use characteristics of households, in addition to transport accessibility statistics.
We will develop a Geographically Weighted Regression (GWR) model to explore the combined spatial variation of fuel and transport poverty patterns across the UK. This model will be applied to three datasets:
- Secondary census and other
- Home Analytics dataset held by EST, in combination with the secondary transport accessibility
- Results from a custom-built face-to-face survey questionnaire.
Analysis of the three datasets will lead to new insights on how fuel poverty patterns also relate to public transport accessibility and journey times, enabling the development of vulnerability scenarios in a variety of spatial situations.
What we are asking
- What are the main socio-spatial factors that determine vulnerability in energy and transport systems in the UK?
Banner photo credit: Annie Spratt on Unsplash