High Spatiotemporal Resolution PM2.5 Concentration Estimation with Machine Learning Algorithm: A Case Study for Wildfire in California

High Spatiotemporal Resolution PM2.5 Concentration Estimation with Machine Learning Algorithm: A Case Study for Wildfire in California

As an aggregate of suspended particulate matter in the air, atmospheric aerosols can affect the regional climate. With the help of satellite remote sensing technology to retrieve AOD (aerosol optical depth) on a global or regional scale, accurate estimation of PM2.5 concentration has become an impor...

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Bibliographic Details
Main Authors: Qian Cui, Feng Zhang, Shaoyun Fu, Xiaoli Wei, Yue Ma, Kun Wu
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Remote Sensing
Subjects:
aerosol optical depth
PM2.5
data fusion
air quality
wildfire
Online Access:https://www.mdpi.com/2072-4292/14/7/1635

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