About the project or challenge area

Using large amounts of new, high-quality satellite data and new machine learning methods, novel ways of understanding the "true" footprint of the city are at hand. However, these new boundaries still need to be validated against existing data on human interaction, behavior, and economic exchange. The project will take novel urban boundaries developed by Wolf & Fox from remote sensing data and examine how coherent the boundaries are with respect to alternative data sources, such as twitter activity or daily movement and commute patterns.

Why choose this opportunity?

You will develop a better understanding of urban data science methods and applications. In addition to training up on cutting-edge methods in urban analytics and using new and interesting datasets, you will have the opportunity to go beyond the traditional spatial analytical methods by applying spatial data science methods to this new data in order to validate the urban boundaries. The student will thus gain a solid domain understanding of urban systems in addition to developing skills in urban data science.

About you

Skills in Python, R, or Julia are preferred. The project is mainly computational and statistical, so prior experience programming will be incredibly useful.

How to apply

All students can apply using the button below, following the Admissions Statement (PDF, 220kB). 

Before applying, we recommend getting in touch with the project's supervisors. If you are interested in this project and would like to learn more about the research you will be undertaking, please use the contact details on this page.