D-DUST: satellites and predictive models against fine particulate matter

“Today, an unimaginable amount of data and observations on the environment are available as open data, and we are especially interested in the information arriving from new satellites monitoring air quality from space”, says Prof. Maria Antonia Brovelli, professor in Geographic Information Systems at Politecnico di Milano. Predictive models, combined with data from satellite platforms, will be particularly decisive in our research into fine particulate matter and their impact on our health, especially for respiratory and cardiovascular diseases.

D-DUST (Data-driven moDelling of particUlate with Satellite Technology aid) is a project designed to investigate the impact that emissions from agriculture and livestock farming have on our health. Financed through “Data Science for Science and Society”, a Call promoted by Fondazione Cariplo, the initiative is assembling Politecnico di Milano, Department of Civil and Environmental Engineering (DICA), as lead partner, with the collaboration of Fondazione Politecnico di Milano, Department of Electronics, Information and Bioengineering (DEIB), and the University of Insubria (DiSAT) as scientific partners.

This study will use data from the Sentinel satellites in the European Copernicus programme, including Sentinel 5P, which maps the main atmospheric pollutants around the globe and provides its measures as open data, and will also investigate spatial predictive models based on machine learning.

To find out more, read the press release