Cargando…
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...
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 |
Ejemplares similares
-
Noninvasive Ultrasound Retinal Stimulation for Vision Restoration at High Spatiotemporal Resolution
por: Qian, Xuejun, et al.
Publicado: (2022) -
Spatiotemporal distribution of ground-level ozone in China at a city level
por: Yang, Guangfei, et al.
Publicado: (2020) -
Spatiotemporal characteristics of ground microtremor in advance of rockfalls
por: Yang, Yi-Rong, et al.
Publicado: (2022) -
Spatiotemporal Variation of Urban Plant Diversity and above Ground Biomass in Haikou, China
por: Zhang, Hai-Li, et al.
Publicado: (2022) -
A robotic sensory system with high spatiotemporal resolution for texture recognition
por: Bai, Ningning, et al.
Publicado: (2023)