Various forms of machine learning (ML) methods have historically played a valuable role in
environmental remote sensing research. With an increasing amount of “big data” from earth …

Particulate matter (PM) is a widely used indicator of air quality. Satellite-derived aerosol
products such as aerosol optical depth (AOD) have been a useful source of data for ground …

Particulate matter with aerodynamic diameters≤ 1 μm (PM1) has a greater impact on the
human health but has been less studied due to fewer ground observations. This study …

Sea surface temperature (SST) is one of the most important parameters in the global ocean-
atmospheric system, changes of which can have profound effects on the global climate and …

Aerosol optical depth (AOD) from polar orbit satellites and meteorological factors have been
widely used to estimate concentrations of surface particulate matter with an aerodynamic …

Being able to monitor PM 2.5 across a range of scales is incredibly important for our ability to
understand and counteract air pollution. Remote monitoring PM 2.5 using satellite-based …

Very high spatially resolved satellite-derived ground-level concentrations of particulate
matter with an aerodynamic diameter of less than 2.5 μm (PM2. 5) have multiple potential …

Abstract Fine particulate matter (PM 2.5) pollution has become a worldwide environmental
concern because of its adverse impacts on human health. This study aimed to explore the …

Sea surface temperature (SST) is an important physical factor in the interaction between the
ocean and the atmosphere. Accurate monitoring and prediction of the temporal and spatial …

The field of forecasting oceanic variables has traditionally relied on numerical models, which
effectively consider the ocean's dynamic evolution and are of physical importance. However …