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...
Published in: | Remote Sensing |
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Main Authors: | , , , , , , , |
Format: | Text |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute
2020
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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. |
format | Text |
genre | Aerosol Robotic Network |
genre_facet | Aerosol Robotic Network |
id | ftmdpi:oai:mdpi.com:/2072-4292/12/6/978/ |
institution | Open Polar |
language | English |
op_collection_id | ftmdpi |
op_coverage | agris |
op_doi | https://doi.org/10.3390/rs12060978 |
op_relation | Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs12060978 |
op_rights | https://creativecommons.org/licenses/by/4.0/ |
op_source | Remote Sensing; Volume 12; Issue 6; Pages: 978 |
publishDate | 2020 |
publisher | Multidisciplinary Digital Publishing Institute |
record_format | openpolar |
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 |