Retrieval of Daily PM<sub>2.5</sub> Concentrations Using Nonlinear Methods: A Case Study of the Beijing–Tianjin–Hebei Region, China

Retrieval of Daily PM<sub>2.5</sub> Concentrations Using Nonlinear Methods: A Case Study of the Beijing–Tianjin–Hebei Region, China

Exposure to fine particulate matter (PM<sub>2.5</sub>) is associated with adverse health impacts on the population. Satellite observations and machine learning algorithms have been applied to improve the accuracy of the prediction of PM<sub>2.5</sub> concentrations. In this s...

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Bibliographic Details
Main Authors: Lijuan Li, Baozhang Chen, Yanhu Zhang, Youzheng Zhao, Yue Xian, Guang Xu, Huifang Zhang, Lifeng Guo
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Remote Sensing
Subjects:
daily PM<sub>2.5</sub> concentrations
remote sensing
MODIS AOD
machine learning algorithm
spatial and temporal distribution
Online Access:https://www.mdpi.com/2072-4292/10/12/2006

Internet

https://www.mdpi.com/2072-4292/10/12/2006

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