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Open AccessArticle

Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China

1
The School of Environment and Geoinformatics, China University of Mining and Technology, Xuzhou 221116, China
2
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, China University of Mining and Technology, Xuzhou 221008, China
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Geomatics in the School of Geoscience and Info-Physics, Central South University, Changsha 410000, China
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Institute of Environmental Physics and Remote Sensing, University of Bremen, 28359 Bremen, Germany
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ROyal Netherlands Meteorological Institute (KNMI), Research and Development (R&D) Satellite Observations, Utrechtseweg 297, 3731GA De Bilt, The Netherlands
6
School of Atmospheric Sciences, Nanjing University of Information Sciences and Technology, Nanjing 210044, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(6), 978; https://doi.org/10.3390/rs12060978
Received: 13 February 2020 / Revised: 12 March 2020 / Accepted: 16 March 2020 / Published: 18 March 2020
(This article belongs to the Special Issue Active and Passive Remote Sensing of Aerosols and Clouds)
Himawari-8 (H8), as a new generation geostationary meteorological satellite, has great potential for monitoring the spatial–temporal variation of aerosol properties. However, the large amount of spectral data with differing observation geometries require re-formulation of the surface reflectance correction to utilize this new satellite data. This is achieved by using an improved version of the time series (TS) technique proposed by Mei et al., (2012) based on the assumption that the ratio of the surface reflectance in different spectral bands does not change between any two scan times within an hour. In addition, more suitable aerosol models were adopted, based on cluster analysis of local Aerosol Robotic Network (AERONET) data. The improved TS algorithm (ITS) was applied to retrieve the Aerosol Optical Depth (AOD) over eastern China and the results compare favorably with collocated reference AOD data at eleven sun photometer sites (R > 0.8, Root Mean Square Error (RMSE) < 0.2). Comparison with the H8 official AOD product and with MODIS Dark Target (DT)–Deep Blue (DB) combined AOD data shows the good performance of the ITS method for AOD retrieval with different observation angles. View Full-Text
Keywords: Himawari-8; aerosol optical depth (AOD); time series; eastern China Himawari-8; aerosol optical depth (AOD); time series; eastern China
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MDPI and ACS Style

Li, D.; Qin, K.; Wu, L.; Mei, L.; de Leeuw, G.; Xue, Y.; Shi, Y.; Li, Y. Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China. Remote Sens. 2020, 12, 978.

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