| Peak Urban

Projects

Machine learning for informal settlement health

Tom Fisher, Mohammad Mamouei, Samuel Yutong Cai, Kazem Rahimi

Machine learning for informal settlement health

This project facilitates data-driven policy making on informal settlements by using machine learning with new sources of data including satellite images.

Informal Cities

Measuring Urban Economics

Samira Barzin, Neave O’Clery

Measuring Urban Economics

This project maps the spatial urban economic dynamics of 14 cities across the global south.

Informal Cities

Mayanka Mukherji, Jin-Ho Chung, Bhawani Buswala, Michael Keith, Tim Schwanen

This project investigates how climate-related migrants secure access to urban infrastructures and services, and how they negotiate living alongside existing residents.

Informal Cities

Pollution and Poverty

Samira Barzin, Neave O’Clery

Pollution and Poverty

This projects combines traditional survey data with satellite derived atmospheric data to shed light on,and seek solutions to, the environmental burdens facing the world's poorest people.

Informal Cities

Big Data driven transport planning and governing in the postcolonial ‘smart city’: A case study of Bangalore

Lucy Baker, Tim Schwanen

Big Data driven transport planning and governing in the postcolonial ‘smart city’

This research explores opportunities to enhance the capacity of transportation governing and planning practices for government institutions, urban planners and transport operators in Bangalore.

Sustainable Cities

Oxford

Spatialising residential neighbourhoods using urban big data

ChengHe Guan , Michael Keith

Spatialising residential neighbourhoods using urban big data

This research aims to provide urban planning and design policy recommendations using urban big data and spatial computation.

City Governance

Oxford

Urban informality and resilience: New methods for old questions

Daniel Straulino, Neave O’Clery

Urban informality and resilience: New methods for old questions

This project uses recent advances in remote sensing and computer vision to develop an alternative approach to obtaining useful data for urban researchers and policy makers.

Sustainable Growth