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3 papers · 2 filters
Estimating regional ground-level PM2.5 directly from satellite top-of-atmosphere reflectance using deep learning
Huanfeng Shen, Tongwen Li, Qiangqiang Yuan +1
Almost all remote sensing atmospheric PM2.5 estimation methods need satellite aerosol optical depth (AOD) products, which are often retrieved from top-of-atmosphere (TOA) reflectan…
The relationships between PM2.5 and meteorological factors in China: Seasonal and regional variations
Qianqian Yang, Qiangqiang Yuan, Tongwen Li +2
The interactions between PM2.5 and meteorological factors play a crucial role in air pollution analysis. However, previous studies that have researched the relationships between PM…
Estimating ground-level PM2.5 by fusing satellite and station observations: A geo-intelligent deep learning approach
Tongwen Li, Huanfeng Shen, Qiangqiang Yuan +2
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 ge…