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20162022
most citedEstimating ground-level PM2.5 by fusing satellite and station observations: A geo-intelligent deep learning approach

417 citations · 921 across the 11 of their papers we have counts for

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Showing physics.ao-phShow all

9 papers · 1 filter

physics.ao-ph2020★ 5 cited

Deep learning-based air temperature mapping by fusing remote sensing, station, simulation and socioeconomic data

Huanfeng Shen, Yun Jiang, Tongwen Li +3

Air temperature (Ta) is an essential climatological component that controls and influences various earth surface processes. In this study, we make the first attempt to employ deep…

physics.ao-ph2018★ 4 cited

Validation approaches for satellite-based PM2.5 estimation: Assessment and a new approach

Tongwen Li, Huanfeng Shen, Qiangqiang Yuan +1

Satellite-derived aerosol optical depth (AOD) has been increasingly employed for the estimation of ground-level PM2.5, which is often achieved by modeling the relationship between…

physics.ao-ph2018★ 111 cited

Evaluation and comparison of MODIS Collection 6.1 aerosol optical depth against AERONET over regions in China with multifarious underlying surfaces

Yuan Wang, Qiangqiang Yuan, Tongwen Li +3

In this study, we evaluated the performance of the MODIS C6.1 AOD products and compared them with the C6 products over regions in China with multifarious underlying surfaces during…

physics.ao-ph2018★ 3 cited

Geographically and temporally weighted neural networks for satellite-based mapping of ground-level PM2.5

Tongwen Li, Huanfeng Shen, Qiangqiang Yuan +1

The integration of satellite-derived aerosol optical depth (AOD) and station-measured PM2.5 provides a promising approach for obtaining spatial PM2.5 data. Several spatiotemporal m…

physics.ao-ph2018★ 5 cited

Real-time and Seamless Monitoring of Ground-level PM2.5 Using Satellite Remote Sensing

Tongwen Li, Chengyue Zhang, Huanfeng Shen +2

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is stil…

physics.ao-ph2017★ 137 cited

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…

physics.ao-ph2017

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…

physics.ao-ph2017★ 417 cited

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…

physics.ao-ph2016★ 232 cited

Point-surface fusion of station measurements and satellite observations for mapping PM2.5 distribution in China: methods and assessment

Tongwen Li, Huanfeng Shen, Chao Zeng +2

Fine particulate matter (PM2.5) is associated with adverse human health effects, and China is currently suffering from serious PM2.5 pollution. To obtain spatially continuous groun…