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

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 cor...

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Published in:Remote Sensing
Main Authors: Ding Li, Kai Qin, Lixin Wu, Linlu Mei, Gerrit de Leeuw, Yong Xue, Yining Shi, Yifei Li
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/rs12060978
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author Ding Li
Kai Qin
Lixin Wu
Linlu Mei
Gerrit de Leeuw
Yong Xue
Yining Shi
Yifei Li
author_facet Ding Li
Kai Qin
Lixin Wu
Linlu Mei
Gerrit de Leeuw
Yong Xue
Yining Shi
Yifei Li
author_sort Ding Li
collection MDPI Open Access Publishing
container_issue 6
container_start_page 978
container_title Remote Sensing
container_volume 12
description 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.
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op_doi https://doi.org/10.3390/rs12060978
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op_rights https://creativecommons.org/licenses/by/4.0/
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/6/978/ 2025-01-16T18:38:11+00:00 Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China Ding Li Kai Qin Lixin Wu Linlu Mei Gerrit de Leeuw Yong Xue Yining Shi Yifei Li agris 2020-03-18 application/pdf https://doi.org/10.3390/rs12060978 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs12060978 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 6; Pages: 978 Himawari-8 aerosol optical depth (AOD) time series eastern China Text 2020 ftmdpi https://doi.org/10.3390/rs12060978 2023-07-31T23:15:16Z 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. Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 12 6 978
spellingShingle Himawari-8
aerosol optical depth (AOD)
time series
eastern China
Ding Li
Kai Qin
Lixin Wu
Linlu Mei
Gerrit de Leeuw
Yong Xue
Yining Shi
Yifei Li
Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China
title Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China
title_full Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China
title_fullStr Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China
title_full_unstemmed Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China
title_short Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China
title_sort himawari-8-derived aerosol optical depth using an improved time series algorithm over eastern china
topic Himawari-8
aerosol optical depth (AOD)
time series
eastern China
topic_facet Himawari-8
aerosol optical depth (AOD)
time series
eastern China
url https://doi.org/10.3390/rs12060978