Pixel-Level Projection of PM<sub>2.5</sub> Using Landsat Images and Cellular Automata Models in the Yangtze River Delta, China

Pixel-Level Projection of PM<sub>2.5</sub> Using Landsat Images and Cellular Automata Models in the Yangtze River Delta, China

In this study, we proposed a pixel-level projection method for fine particulate matter (PM<sub>2.5</sub>) over a long term and across a large area using a combination of Landsat images, PM<sub>2.5</sub> data from monitoring stations, and historical gridded PM<sub>2.5<...

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Bibliographic Details
Main Authors:	Panli Tang, Yongjiu Feng, Xiaohua Tong, Mengrong Xi, Pengshuo Li, Shurui Chen, Rong Wang, Xiong Xu, Chao Wang, Peng Chen
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Series:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:	Cellular automata (CA) fine particulate matter (PM<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_2.5$</tex-math> </inline-formula> </named-content>) land-use change pixel-level projection spatial lag model (SLM) Yangtze River Delta (YRD)
Online Access:	https://ieeexplore.ieee.org/document/10184023/

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https://ieeexplore.ieee.org/document/10184023/