An Ensemble Machine-Learning Model To Predict Historical PM2.5Concentrations in China from Satellite Data

Qingyang Xiao; Howard H. Chang; Guannan Geng; Yang Liu

doi:10.1021/acs.est.8b02917

journal article Oct 24, 2018

An Ensemble Machine-Learning Model To Predict Historical PM2.5Concentrations in China from Satellite Data

Qingyang Xiao

Howard H. Chang

Guannan Geng

Yang Liu

Environmental Science & Technology Vol. 52 No. 22 pp. 13260-13269 · American Chemical Society (ACS)

View at Publisher Save 10.1021/acs.est.8b02917

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References

Details

Published: Oct 24, 2018
Vol/Issue: 52(22)
Pages: 13260-13269

Authors

Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA

Southwest University

Funding

National Aeronautics and Space Administration Award: NNX16AQ28G

National Institute of Environmental Health Sciences Award: R01 ES027892

Cite This Article

Qingyang Xiao, Howard H. Chang, Guannan Geng, et al. (2018). An Ensemble Machine-Learning Model To Predict Historical PM2.5Concentrations in China from Satellite Data. Environmental Science & Technology, 52(22), 13260-13269. https://doi.org/10.1021/acs.est.8b02917

An Ensemble Machine-Learning Model To Predict Historical PM2.5Concentrations in China from Satellite Data

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