Remote Sensing Fine Estimation Model of PM<sub>2.5</sub> Concentration Based on Improved Long Short-Term Memory Network: A Case Study on Beijing–Tianjin–Hebei Urban Agglomeration in China

Remote Sensing Fine Estimation Model of PM<sub>2.5</sub> Concentration Based on Improved Long Short-Term Memory Network: A Case Study on Beijing–Tianjin–Hebei Urban Agglomeration in China

The accurate prediction of PM<sub>2.5</sub> concentration across extensive temporal and spatial scales is essential for air pollution control and safeguarding public health. To address the challenges of the uneven coverage and limited number of traditional PM<sub>2.5</sub> gr...

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Bibliographic Details
Main Authors: Yiye Ji, Yanjun Wang, Cheng Wang, Xuchao Tang, Mengru Song
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
Subjects:
MODIS AOD
self-adaptive attention mechanism
long and short-term memory network
deep learning
PM<sub>2.5</sub> concentration prediction
Online Access:https://www.mdpi.com/2072-4292/16/22/4306
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