AI4SmartCities CCN3
The ESA project Artificial Intelligence for Smart Cities (AI4SC) CCN3, led by the German Aerospace Centre (DLR), is developing global indicators to systematically record and evaluate the effects of rapid urbanisation. In close consultation with users, key requirements have been identified: more frequently updated data to map urban dynamics – especially in fast-growing regions –, more accurate population estimates with a high level of spatial detail, and improved analyses of exposure and vulnerability to natural hazards such as floods, heat waves and earthquakes. The project specifically addresses these needs and supports international actors, including the World Bank, in issues of urban resilience and sustainable development.
At the core of the project is the World Settlement Footprint Tracker (WSF® tracker) – a globally consistent dataset on settlement extent at 10m resolution, which is updated every six months and covers the period from July 2016 to January 2027. In addition, a multitemporal WSF® Population dataset is being developed to provide biannual, high-resolution population information. The initial focus is on the Global South, with a perspective expansion towards a global coverage.
Based on these datasets, statistical indicators are derived that quantify settlement growth, population distribution, and risk and vulnerability patterns at different spatial levels, including administrative boundaries and HEALPix cells. In addition, a web-based geo-platform is being developed that enables interactive visualisation, graphical analysis, and download functions. Raster data will be provided via XYZ tile services, while integrated analyses will be accessible through an API. This modular architecture supports flexible reuse of the data and promotes evidence-based decision-making in urban planning, environmental monitoring, policy advice and risk management.