Spatial Analysis in Identifying and Characterising Gentrification in London
Technology Category
- Analytics & Modeling - Machine Learning
Applicable Industries
- Cities & Municipalities
- Equipment & Machinery
Use Cases
- Smart City Operations
About The Customer
The Centre for Advanced Spatial Analysis (CASA) is an interdisciplinary research institute that focuses on the science of cities. It is part of The Bartlett Faculty of the Built Environment at UCL. CASA uses geospatial analysis to tackle a number of challenges related to urban development and transformation. One of their key areas of interest is the phenomenon of gentrification, where they aim to identify, characterise, and predict its occurrence in different neighborhoods within the city of London.
The Challenge
The Centre for Advanced Spatial Analysis (CASA) at UCL was faced with the challenge of identifying, characterising, and locating neighborhoods in London that have recently undergone gentrification. They needed to disaggregate the different types of changes revealed by the data. Additionally, they aimed to predict which neighborhoods are likely to be the next targets of gentrification. The ultimate goal was to present and make available data, code, and novel interactive visualisations as a comprehensive tool for supporting policy and decision making in the city.
The Solution
CASA turned to CARTO, a platform known for its ability to leverage novel Machine Learning, spatial analytical techniques, and new sources of multi-dimensional data. CARTO was used to create novel interactive visualisations that would help in the identification and characterisation of gentrified neighborhoods. The platform's advanced capabilities allowed CASA to not only identify areas that have undergone gentrification but also predict which neighborhoods are likely to be next. The data, code, and visualisations created using CARTO served as a comprehensive tool for supporting policy and decision making in the city.
Operational Impact
Quantitative Benefit
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