Esra Suel, Meytar Sorek-Hamer, Izabela Moise, Michael von Pohle, Adwait Sahasrabhojanee, Ata Akbari Asanjan, Raphael E Arku, Abosede S Alli, Benjamin Barratt, Sierra N Clark, Ariane Middel, Emily Deardorff, Violet Lingenfelter, Nikunj Oza, Nishant Yadav, Majid Ezzati, Michael Brauer
High spatial resolution information on urban air pollution levels is unavailable in many areas globally, partially due to high input data needs of existing estimation approaches. Here we introduce a computer vision method to estimate annual means for air pollution levels from street level images. We used annual mean estimates of NO2 and PM2.5 concentrations from locally calibrated models as labels from London, New York, and Vancouver to allow for compilation of a sufficiently large dataset (~250k images for each city)...
July 17, 2022: Remote Sensing