Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data
High temporal resolution aerosol optical depth (AOD) products are very important for the studies of atmospheric environment and climate change. Geostationary Ocean Color Imager (GOCI) is a suitable data source for AOD retrieval, as it can monitor hourly aerosol changes and make up for the low tempor...
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doaj-5b1ca909d1e64309afaeab007910bb932021-07-01T00:30:10ZengMDPI AGRemote Sensing2072-42922021-06-01132376237610.3390/rs13122376Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing DataLijuan Chen0Ying Fei1Ren Wang2Peng Fang3Jiamei Han4Yong Zha5Key Laboratory of Virtual Geographic Environment of Ministry of Education, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographic Science, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment of Ministry of Education, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographic Science, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment of Ministry of Education, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographic Science, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment of Ministry of Education, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographic Science, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment of Ministry of Education, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographic Science, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment of Ministry of Education, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographic Science, Nanjing Normal University, Nanjing 210023, ChinaHigh temporal resolution aerosol optical depth (AOD) products are very important for the studies of atmospheric environment and climate change. Geostationary Ocean Color Imager (GOCI) is a suitable data source for AOD retrieval, as it can monitor hourly aerosol changes and make up for the low temporal resolution deficiency of polar orbiting satellite. In this study, we proposed an algorithm for retrieving high temporal resolution AOD using GOCI data and then applied the algorithm in the Yangtze River Delta, a typical region suffering severe air pollution issues. Based on Moderate-resolution Imaging Spectroradiometer (MODIS) surface reflectance determined by MODIS V5.2 algorithm and MODIS Bidirectional Reflectance Distribution Function (BRDF) data, after spectral conversion between MODIS and GOCI, the GOCI surface reflectance at different solar angles were obtained and used to retrieve AOD. Five indicators including correlation coefficient (R), significant level of the correlation (<i>p</i> value), mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) were employed to analyze the errors between the Aerosol Robotic Network (AERONET) observed AOD and the GOCI retrieved AOD. The results showed that the GOCI AOD retrieved by the continental aerosol look-up table was consistent with the AERONET AOD (R > 0.7, <i>p</i> ≤ 0.05). The highest R value of Taihu Station and Xuzhou CUMT Station are both 0.84 (8:30 a.m.); the minimum RMSE at Taihu and Xuzhou-CUMT stations were 0.2077 (11:30 a.m.) and 0.1937 (10:30 a.m.), respectively. Moreover, the results suggested that the greater the solar angle of the GOCI sensor, the higher the AOD retrieval accuracy, while the retrieved AOD at noon exhibited the largest error as assessed by MAE and MRE. We concluded that the inaccurate estimation of surface reflectance was the root cause of the retrieval errors. This study has implications in providing a deep understanding of the effects of solar angle changes on retrieving AOD using GOCI.https://www.mdpi.com/2072-4292/13/12/2376aerosol optical depthhigh resolutionspectral conversionGOCIMODIS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lijuan Chen Ying Fei Ren Wang Peng Fang Jiamei Han Yong Zha |
spellingShingle |
Lijuan Chen Ying Fei Ren Wang Peng Fang Jiamei Han Yong Zha Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data Remote Sensing aerosol optical depth high resolution spectral conversion GOCI MODIS |
author_facet |
Lijuan Chen Ying Fei Ren Wang Peng Fang Jiamei Han Yong Zha |
author_sort |
Lijuan Chen |
title |
Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data |
title_short |
Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data |
title_full |
Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data |
title_fullStr |
Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data |
title_full_unstemmed |
Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data |
title_sort |
retrieval of high temporal resolution aerosol optical depth using the goci remote sensing data |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2021-06-01 |
description |
High temporal resolution aerosol optical depth (AOD) products are very important for the studies of atmospheric environment and climate change. Geostationary Ocean Color Imager (GOCI) is a suitable data source for AOD retrieval, as it can monitor hourly aerosol changes and make up for the low temporal resolution deficiency of polar orbiting satellite. In this study, we proposed an algorithm for retrieving high temporal resolution AOD using GOCI data and then applied the algorithm in the Yangtze River Delta, a typical region suffering severe air pollution issues. Based on Moderate-resolution Imaging Spectroradiometer (MODIS) surface reflectance determined by MODIS V5.2 algorithm and MODIS Bidirectional Reflectance Distribution Function (BRDF) data, after spectral conversion between MODIS and GOCI, the GOCI surface reflectance at different solar angles were obtained and used to retrieve AOD. Five indicators including correlation coefficient (R), significant level of the correlation (<i>p</i> value), mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) were employed to analyze the errors between the Aerosol Robotic Network (AERONET) observed AOD and the GOCI retrieved AOD. The results showed that the GOCI AOD retrieved by the continental aerosol look-up table was consistent with the AERONET AOD (R > 0.7, <i>p</i> ≤ 0.05). The highest R value of Taihu Station and Xuzhou CUMT Station are both 0.84 (8:30 a.m.); the minimum RMSE at Taihu and Xuzhou-CUMT stations were 0.2077 (11:30 a.m.) and 0.1937 (10:30 a.m.), respectively. Moreover, the results suggested that the greater the solar angle of the GOCI sensor, the higher the AOD retrieval accuracy, while the retrieved AOD at noon exhibited the largest error as assessed by MAE and MRE. We concluded that the inaccurate estimation of surface reflectance was the root cause of the retrieval errors. This study has implications in providing a deep understanding of the effects of solar angle changes on retrieving AOD using GOCI. |
topic |
aerosol optical depth high resolution spectral conversion GOCI MODIS |
url |
https://www.mdpi.com/2072-4292/13/12/2376 |
work_keys_str_mv |
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