Analysis of Primary Air Pollutants’ Spatiotemporal Distributions Based on Satellite Imagery and Machine-Learning Techniques

Analysis of Primary Air Pollutants’ Spatiotemporal Distributions Based on Satellite Imagery and Machine-Learning Techniques

Accurate monitoring of air pollution is crucial to human health and the global environment. In this research, the various multispectral satellite data, including MODIS AOD/SR, Landsat 8 OLI, and Sentinel-2, together with the two most commonly used machine-learning models, viz. multi-layer backpropag...

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Bibliographic Details
Main Authors: Yanyu Li, Meng Zhang, Guodong Ma, Haoyuan Ren, Ende Yu
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Atmosphere
Subjects:
machine learning
multispectral satellite data
aerosol optical depth
surface reflectance
air pollutant
spatiotemporal distribution
Online Access:https://www.mdpi.com/2073-4433/15/3/287

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