基于GF-4卫星的长三角城市群PM<sub>2.5</sub>遥感反演

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Abstract This paper used 6 SV model and dark target algorithm to retrieve AOD with a high spatial resolution based on GaoFen-4(GF-4) geostationary satellite data. Afterwards, combined with the PM_2.5 concentration data of the ground air quality observation sites, meteorological factors and other data, physical correction methods and linear mixed effects(LME) model were used to monitor the large-scale and spatial continuous PM_2.5 concentration in the Yangtze River Delta urban agglomeration(YRDUA). The results showed that the retrieved GF-4 AOD has good spatial resolution and spatial continuity, and the correlation coefficient(R) with AERONET ground-based monitoring data reached 0.82. The LME model based on GF-4 AOD showed a good agreement between the estimated PM_2.5 concentration and the in situ observed values(R²=0.74). The 10-fold cross-validation R² of spring, summer,autumn and winter were 0.67, 0.59, 0.64 and 0.72, respectively; and the mean absolute error(MAE) were 10.40, 7.42, 10.10 and 13.34μg/m³, respectively, which indicates that GF-4 can be used for regional PM_2.5 concentration monitoring.

Key words： GF-4 satellite PM_2.5 AOD remote sensing Yangtze River Delta urban agglomeration(YRDUA)

Received: 10 August 2021

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X513

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	Articles by authors
	YAN Ying-ting
	LU Xiao-man
	WANG Jia-jia
	CHEN Ming-nan
	ZHOU Li-guo
	MA Yu-chun

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YAN Ying-ting,LU Xiao-man,WANG Jia-jia等. Remote estimation of PM_2.5 based on GaoFen-4 satellite data in the Yangtze River Delta urban agglomeration[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(3): 1005-1012.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I3/1005

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