Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting
Abstract Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM2.5 is a promising way to fill the areas that are not covered by ground PM2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) a...
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2017
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| Accès en ligne: | https://doaj.org/article/38379f76c318465b87bbed02f065fc88 |
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