Social Data from Space as the Choice of “First Resort”

About this Talk

This talk will try to convince you that satellite data are more than “surrogates of last resort” for conducting cutting edge social science. Traditionally, the study of social systems has relied on bespoke data infrastructures such as censuses, surveys, and manual collection of fine grained geospatial data. Although these are relevant and important, I will argue that their value proposition can be augmented by combining (and, in some instances, replacing) them with observations derived from satellite data. This shift has only become possible recently thanks to advances in remote sensing, artificial intelligence, and computational technology. After illustrating the confluence of these trends with examples that are already possible today, focused on understanding cities and their evolution, the talk will conclude with a brief overview of Imago, the Smart Data Research UK data service for imagery, which is working to operationalise this vision in the UK.

About the Speaker

Dani Arribas-Bel is interested in computers, cities, and data. He is Professor in Geographic Data Science at the University of Liverpool, and co-director of Imago, the Smart Data Research UK Imagery Data Service. From 2022 to 2025, he was Deputy Programme Director for Urban Analytics at The Alan Turing, where he also held a joint Turing/ESRC fellowship from 2020 to 2023. Prior to arriving at Liverpool in 2015, Dani held positions at the University of Birmingham (UK), the VU University in Amsterdam (Netherlands), Arizona State University (US), and Universidad de Zaragoza (Spain). He holds honorary positions at the University of Chicago’s Center for Spatial Data Science, and the Center for Open Geographical Science of San Diego State University. Dani’s research combines modern computation with new forms of data to shed light on the spatial structure(s) of cities. His research is published in journals such as PLOS ONE, Demography, Geographical Analysis, or Environment and Planning (A/B/C). Together with Serge Rey and Levi Wolf, he is the author of “Geographic Data Science with Python”, published by CRC Press in 2023. Dani currently serves as co-editor of the journal “Environment and Planning B - Urban Analytics & City Science”, where he co-founded the Urban Data/Code section.

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