Exploring how AI, geospatial data, and emerging digital data can help us understand cities, populations, and places.
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Nairobi, Kenya
Visible Waste, Invisible Inequality
With APHRC, UN-Habitat, KDI, and Community Mappers
Funded by UCL Global Engagement Funds (GEF)
Developing an AI-based urban monitoring framework to map visible waste and identify spatial gaps in conventional urban data.
Nairobi, Kenya
Revealing Digitally Invisible Groups
Combining satellite, building, social-media and street-view data to examine how different urban environments are represented in AI-based land-use classification.
Kenya & Mexico
Can We Predict Internet Connectivity?
Testing how well machine-learning and spatial models predict internet connectivity within cities and across countries.
Gaza
Satellite-Based Tent Detection for Population Estimation
Real Good Research · Ongoing
Using computer vision on satellite imagery to detect tents and estimate population where conventional data are scarce.
Chile–United States & Turkey–Germany
Detecting Migration Surges with Digital Trace Data
Using digital trace data to measure how policy changes shift cross-border migration, including onward flows about 240% higher for Chile→US and 122% higher for Turkey→Germany than synthetic controls.
Euboea, Greece
Wildfire Detection and Forest Management
Funded by the Interdisciplinary School for Environmental Crisis (ISEC)
Designing a satellite-based system for early wildfire detection, and assessing forest management and community preparedness.
Peak District, United Kingdom
Land Cover Change Detection
Funded by The Alan Turing Institute
Using deep learning and satellite imagery to detect land-cover change.
United Kingdom
Funded by the BBC · Ongoing
Linking the places people like and dislike to neighbourhood deprivation, local amenities, and residents’ comments.