A Deep Learning Approach for Meter-Scale Air Quality Estimation in Urban Environments Using Very High-Spatial-Resolution Satellite Imagery

A Deep Learning Approach for Meter-Scale Air Quality Estimation in Urban Environments Using Very High-Spatial-Resolution Satellite Imagery

High-spatial-resolution air quality (AQ) mapping is important for identifying pollution sources to facilitate local action. Some of the most populated cities in the world are not equipped with the infrastructure required to monitor AQ levels on the ground and must rely on other sources, such as sate...

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Bibliographic Details
Main Authors: Meytar Sorek-Hamer, Michael Von Pohle, Adwait Sahasrabhojanee, Ata Akbari Asanjan, Emily Deardorff, Esra Suel, Violet Lingenfelter, Kamalika Das, Nikunj C. Oza, Majid Ezzati, Michael Brauer
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Atmosphere
Subjects:
air quality
remote sensing
urban environment
deep learning
satellite imagery
Online Access:https://www.mdpi.com/2073-4433/13/5/696

Internet

https://www.mdpi.com/2073-4433/13/5/696

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