Artificial Intelligence, Digitalisation, New Data

Revealing urban transformations with AI and satellite imagery

4 minute read

By Alexandre Banquet (, Centre for Entrepreneurship, SMEs, Regions and Cities (OECD)

Monitoring land use patterns across OECD metropolitan areas

The role of satellite imagery and AI

Observing cities from space

Figure 1: Information captured by satellite imagery for the city of Luxembourg

Source: ESA Sentinel-1 and Sentinel-2

Figure 2: Land use prediction pipeline

Figure 3: Example of built-up expansion detected for the town of Naas, Ireland


Banquet, A., et al. (2022), “Monitoring land use in cities using satellite imagery and deep learning”, OECD Regional Development Papers, No. 28, OECD Publishing, Paris,

OECD/European Commission (2020), Cities in the World: A New Perspective on Urbanisation, OECD Urban Studies, OECD Publishing, Paris,

Schiavina M., Freire S., Carioli A., MacManus K. (2023): GHS-POP R2023A – GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC), PID:, doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE

  1. Cities are here defined as high-density places of at least 50,000 inhabitants.