Since the mid-1990s a new generation of Earth-observing satellites has been able to detect
tropospheric air pollution at increasingly high spatial and temporal resolution. Most primary …

The recent literature on satellite remote sensing of air quality is reviewed. 2009 is the 50th
anniversary of the first satellite atmospheric observations. For the first 40 of those years …

Abstract Fine particulate matter (PM 2.5) is closely related to the atmospheric environment
and human life. Satellite-based aerosol optical depth (AOD) products have been widely …

To estimate PM2. 5 concentrations, many parametric regression models have been
developed, while nonparametric machine learning algorithms are used less often and …

Learning incorporates a broad range of complex procedures. Machine learning (ML) is a
subdivision of artificial intelligence based on the biological learning process. The ML …

Fusing satellite observations and station measurements to estimate ground‐level PM2. 5 is
promising for monitoring PM2. 5 pollution. A geo‐intelligent approach, which incorporates …

The past five decades have witnessed satellite remote sensing become one of most efficient
tools for surveying the Earth at local, regional, and global spatial scales. These space-based …

Estimating ground-level PM2. 5 from satellite-derived aerosol optical depth (AOD) using a
spatial statistical model is a promising new method to evaluate the spatial and temporal …

Although ground-level monitoring can provide accurate PM 2.5 measurements, it has limited
spatial coverage and resolution. In contrast, satellite-based monitoring can provide aerosol …

Fine particulate matter with a diameter of less than 2.5 µ m (PM 2.5) has been used as an
important atmospheric environmental parameter mainly because of its impact on human …