Aerosol Retrieval Method Using Multi-Angle Data from GF-5 02 DPC over the Jing–Jin–Ji Region

The Directional Polarimetric Camera (DPC) aboard the Chinese GaoFen-5 02 satellite is designed to monitor aerosols and particulate matter (PM). In this study, we retrieved the aerosol optical depth (AOD) over the Jing–Jin–Ji (JJJ) region using multi-angle data from the DPC, employing a combination of dark dense vegetation (DDV) and multi-angle retrieval methods. The added value of our method included novel hybrid methodology and good practical performance. The retrieval process involves three main steps: (1) deriving AOD from DPC data collected at the nadir angle using linear parameters of land surface reflectance between the blue and red bands from the MOD09 surface product; (2) after performing atmospheric correction with the retrieved AOD, calculating the variance of the normalized reflectance at all observation angles; and (3) leveraging the calculated variance to obtain the final AOD values. AOD images over the JJJ region were successfully retrieved from DPC data collected between January and June 2022. To validate the retrieval method, we compared our results with aerosol products from the AErosol RObotic NETwork (AERONET) Beijing-RADI site, as well as aerosol data from MODerate-resolution Imaging Spectroradiometer (MODIS) and the generalized retrieval of atmosphere and surface properties (GRASP)/models over the same site. In terms of validation metrics, the correlation coefficient (R2) and root mean square error (RMSE) indicated that our method achieved high accuracy, with an R2 value greater than 0.9 and an RMSE below 0.1, closely aligning with the performance of GRASP.

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Publication Details

Journal
Remote Sensing
Published
2025-04-16
DOI
https://doi.org/10.3390/rs17081415
Citations
2
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
2.21

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article

Aerosol Retrieval Method Using Multi-Angle Data from GF-5 02 DPC over the Jing–Jin–Ji Region

Chunyan Zhou, Huayou Li, Cheng Chen, Shikuan Jin et al.
2 citations
Remote Sensing
Atmospheric aerosols and clouds
2.21
article

Aerosol Retrieval Method Using Multi-Angle Data from GF-5 02 DPC over the Jing–Jin–Ji Region

Chunyan Zhou, Huayou Li, Cheng Chen, Shikuan Jin, Zhongting Wang, Siyao Zhai, Ruijie Zhang, Zhen Liu, Hui Chen
article en
2 citations

Abstract

The Directional Polarimetric Camera (DPC) aboard the Chinese GaoFen-5 02 satellite is designed to monitor aerosols and particulate matter (PM). In this study, we retrieved the aerosol optical depth (AOD) over the Jing–Jin–Ji (JJJ) region using multi-angle data from the DPC, employing a combination of dark dense vegetation (DDV) and multi-angle retrieval methods. The added value of our method included novel hybrid methodology and good practical performance. The retrieval process involves three main steps: (1) deriving AOD from DPC data collected at the nadir angle using linear parameters of land surface reflectance between the blue and red bands from the MOD09 surface product; (2) after performing atmospheric correction with the retrieved AOD, calculating the variance of the normalized reflectance at all observation angles; and (3) leveraging the calculated variance to obtain the final AOD values. AOD images over the JJJ region were successfully retrieved from DPC data collected between January and June 2022. To validate the retrieval method, we compared our results with aerosol products from the AErosol RObotic NETwork (AERONET) Beijing-RADI site, as well as aerosol data from MODerate-resolution Imaging Spectroradiometer (MODIS) and the generalized retrieval of atmosphere and surface properties (GRASP)/models over the same site. In terms of validation metrics, the correlation coefficient (R2) and root mean square error (RMSE) indicated that our method achieved high accuracy, with an R2 value greater than 0.9 and an RMSE below 0.1, closely aligning with the performance of GRASP.

Remote SensingVol. 17(8)
Chinese Academy of Sciences (CN), North China University of Water Resources and Electric Power (CN), Ministry of Ecology and Environment (CN), Hefei Institutes of Physical Science (CN), China University of Geosciences (CN), Anhui Institute of Optics and Fine Mechanics (CN), Chinese Research Academy of Environmental Sciences (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, China Scholarship Council
Openalex Percentile: Top 14%
Atmospheric aerosols and clouds
2.21
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