Case Study: UCL achieves deeper insight into UK gentrification with CARTO

Using Spatial Analysis to Measure UK Gentrification

UCL’s Centre for Advanced Spatial Analysis (CASA) needed to identify and map recent gentrification in London, distinguish different types of neighborhood change, and predict areas likely to change next. They also wanted a way to share data, code, and interactive visualizations to support policy and city decision-making, and they used CARTO for spatial analysis and visualization.

CARTO helped CASA apply machine learning, spatial analytics, and multidimensional data to build interactive tools for the study. The results showed that neighborhood ascent and decline affected 1,351 LSOAs, or nearly 30% of London’s LSOAs, with every borough except the City of London impacted, highlighting the scale of socio-spatial change across the city.

UCL