Next Article in Journal
Surface Water Quality Analysis Using CORINE Data: An Application to Assess Reservoirs in Poland
Previous Article in Journal
3D Displacement Field of Wenchuan Earthquake Based on Iterative Least Squares for Virtual Observation and GPS/InSAR Observations
Previous Article in Special Issue
Analysis of the Transport of Aerosols over the North Tropical Atlantic Ocean Using Time Series of POLDER/PARASOL Satellite Data
Open AccessArticle

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

The School of Environment and Geoinformatics, China University of Mining and Technology, Xuzhou 221116, China
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, China University of Mining and Technology, Xuzhou 221008, China
Geomatics in the School of Geoscience and Info-Physics, Central South University, Changsha 410000, China
Institute of Environmental Physics and Remote Sensing, University of Bremen, 28359 Bremen, Germany
ROyal Netherlands Meteorological Institute (KNMI), Research and Development (R&D) Satellite Observations, Utrechtseweg 297, 3731GA De Bilt, The Netherlands
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;
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
Show Figures

Graphical abstract

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.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop