U-GEO is an algorithm based on machine learning that combines Copernicus data with urban planning, resource management, and green infrastructure. It is designed to help create efficient green infrastructure and continuously monitor vegetation health conditions and performance. The Copernicus data is used to correlate current vegetation planting in different urban environments with key performance parameters related to air pollution reduction, heat island minimisation, and biodiversity preservation. The U-GEO algorithm is then employed to determine the optimal distribution of green infrastructure and maximise the key performance parameters while implementing urban planning and an economical budget as boundaries. The second part of the system is based upon the continuous monitoring of green infrastructure through the daily information gathered by Copernicus satellites. This enables targeted onsite maintenance should the health conditions of urban vegetation or the efficiency of green infrastructure decrease.
Federico Ferroni, Andrea Mastropietro,
Flavio Proietti, Giuseppe Pilato