Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations | Zendy

Xiaofan Xing | Zendy; Yuankang Xiong | Zendy; Ruipu Yang | Zendy; Rong Wang | Zendy; Weibing Wang | Zendy; Haidong Kan | Zendy; Tun Lu | Zendy; Dongsheng Li | Zendy; Junji Cao | Zendy; Josep Peñuelas | Zendy; Philippe Ciais | Zendy; Nico Bauer | Zendy; Oliviér Boucher | Zendy; Yves Balkanski | Zendy; Didier Hauglustaine | Zendy; Guy Brasseur | Zendy; Lidia Morawska | Zendy; Ivan A. Janssens | Zendy; Xiangrong Wang | Zendy; Jordi Sardans | Zendy; Yijing Wang | Zendy; YiFei Deng | Zendy; Lin Wang | Zendy; Jianmin Chen | Zendy; Xu Tang | Zendy; Renhe Zhang | Zendy

Open Access

Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations

Author(s) -

Xiaofan Xing,

Yuankang Xiong,

Ruipu Yang,

Rong Wang,

Weibing Wang,

Haidong Kan,

Tun Lu,

Dongsheng Li,

Junji Cao,

Josep Peñuelas,

Philippe Ciais,

Nico Bauer,

Oliviér Boucher,

Yves Balkanski,

Didier Hauglustaine,

Guy Brasseur,

Lidia Morawska,

Ivan A. Janssens,

Xiangrong Wang,

Jordi Sardans,

Yijing Wang,

YiFei Deng,

Lin Wang,

Jianmin Chen,

Xu Tang,

Renhe Zhang

Publication year - 2021

Publication title -

proceedings of the national academy of sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 5.011

H-Index - 771

eISSN - 1091-6490

pISSN - 0027-8424

DOI - 10.1073/pnas.2109098118

Subject(s) - covid-19 , satellite , meteorology , environmental science , air pollution , pollution , atmospheric sciences , remote sensing , computer science , physics , geography , virology , astronomy , chemistry , infectious disease (medical specialty) , biology , medicine , outbreak , disease , pathology , ecology , organic chemistry

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