Ground-Level NO(2) Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence

[Image: see text] Nitrogen dioxide (NO(2)) at the ground level poses a serious threat to environmental quality and public health. This study developed a novel, artificial intelligence approach by integrating spatiotemporally weighted information into the missing extra-trees and deep forest models to...

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Detalles Bibliográficos
Autores principales: Wei, Jing, Liu, Song, Li, Zhanqing, Liu, Cheng, Qin, Kai, Liu, Xiong, Pinker, Rachel T., Dickerson, Russell R., Lin, Jintai, Boersma, K. F., Sun, Lin, Li, Runze, Xue, Wenhao, Cui, Yuanzheng, Zhang, Chengxin, Wang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301922/
https://www.ncbi.nlm.nih.gov/pubmed/35767687
http://dx.doi.org/10.1021/acs.est.2c03834

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301922/
https://www.ncbi.nlm.nih.gov/pubmed/35767687
http://dx.doi.org/10.1021/acs.est.2c03834

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