ESTIMATION OF HOURLY PM2.5 MASS CONCENTRATION FROM GEOSTATIONARY SATELLITE AEROSOL OPTICAL DEPTH DATA

被引：0

作者：

Sun, Yuxin ^{[1
]}

Xue, Yong ^{[1
,2
]}

Cui, Tengfei ^{[1
]}

Jiang, Xingxing ^{[1
]}

Wu, Shuhui ^{[1
]}

Jin, Chunlin ^{[1
]}

机构：

[1] China Univ Min & Technol, Sch Environm & Spatial Informat, Xuzhou 221116, Jiangsu, Peoples R China

[2] Univ Derby, Sch Elect Comp & Math, Coll Engn & Technol, Kedleston Rd, Derby DE22 1GB, England

来源：

IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2023年

基金：

中国国家自然科学基金;

关键词：

Remote Sensing; Geostationary satellite; PM2.5; AOD; PM10;

D O I：

10.1109/IGARSS52108.2023.10283127

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Remote sensing inversion of global PM2.5 is an important research topic. In the present study, the Aerosol Optical Depth (AOD) dataset was established by four geostationary satellites to estimate global PM2.5 concentrations using improved Geographic Time-Weighted Regression model (IGTWR) models. Then a global hourly PM2.5 concentration dataset was obtained in May 2020. The estimated result for PM2.5 is verified at ground stations with R of 0.71 and RMSE (Root Mean Square Error) of 26.6 mu g/m(3). The results indicate that PM2.5 has obvious spatial and temporal distribution in the world.

引用

页码：1065 / 1067

页数：3

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